Top 9 Must-Have Functionalities for Web and Mobile Applications

The year 2023 is when technology continues to overturn the existing order of things in the digital environment. Developers look for new ways to push development boundaries every year. From web development to machine learning, the languages we'll discuss today offer a wide range of possibilities and allow developers to turn their creative ideas into reality.

The most popular programming languages in 2023

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Languages, once considered groundbreaking, are becoming the standard, while new versions are constantly emerging to meet the needs of the most demanding projects of all sizes. The rapid development of the digital world in all areas of business and industries leads to a constant demand for powerful programming languages that can be used to create innovative products that simplify the work processes of any business. And also increasing the level of efficiency through the automation of work processes.

In this dynamic programming landscape, some languages are rapidly gaining popularity because of their strengths and ability to meet modern developers' needs. At the same time, some traditional languages remain relevant and continue to play an essential role in the programming world. It is important not to lose the balance between "classics" and new languages that complement the development process and make it more straightforward.

We analyze the top programming languages shaping the technology landscape of 2023 and enabling developers to build high-performance applications, create intelligent algorithms and machine learning, develop web applications, and process massive amounts of data.

Whether you're a seasoned programmer or just starting out in the development world, these popular languages offer you the opportunity to explore new horizons in technology. Let's take a look at what programming languages are worth learning and using in 2023 to stay at the forefront of innovation and successfully implement your projects.

• Python continues to hold its position as one of the most popular programming languages. With its simple syntax, Python is ideal for developing web applications, data analysis, machine learning, and artificial intelligence. With an extensive ecosystem of libraries such as NumPy, Pandas, TensorFlow, and PyTorch, it provides powerful tools to solve diverse problems.

• JavaScript remains an integral part of web development and continues to hold an important place in the programming world. Because of its versatility and widespread use in frontend and backend development, JavaScript is a significant component for creating interactive user interfaces and web applications. Frameworks and libraries such as React, Angular, and Vue.js make developing JavaScript web applications effortless.

• Java is one of the most popular programming languages, especially in enterprise environments. Because of its reliability, portability, and extensive support from the developer community, Java is used to develop scalable applications, web services, and mobile applications on the Android platform. Java also offers a rich selection of frameworks, such as Spring, that simplify application development and management.

• TypeScript, a programming language built on top of JavaScript, will continue to gain popularity in 2023. It adds static typing to JavaScript, which helps developers identify errors at compile time and create more robust code. TypeScript is widely used to develop large projects and applications. Its support in popular integrated development environments (IDEs) such as Visual Studio Code makes it an attractive choice for many developers.

• Go (or Golang) is a relatively new programming language gaining popularity in 2023. Developed at Google, Go provides simplicity and efficiency, enabling the creation of high-performance applications and services. Because of its competitive performance and ability to scale quickly, Go is often used to create web servers, micro-services architecture, and big data processing.
  

Summary

These five programming languages are leading the development world this year. They provide developers with powerful tools for creating various applications and solutions, including web apps, mobile apps, and large-scale digital projects. The choice of programming language depends on the specific needs of the project and the developer's preferences. Still, these five leaders provide a solid foundation for success in today's technology environment.

The technological landscape is constantly changing, and programming languages are also evolving. New languages emerge, and existing ones are updated and adapted to changing needs. Therefore, developers need to remain flexible, adapt to the rapidly changing technological environment, keep abreast of the latest trends, and learn new technologies and programming languages to successfully implement projects of any complexity.

In 2024 alone, the medical imaging software market size reached $8.11B. By 2029, it is projected to grow to $11.83B and up to 7.84% at a CAGR. This is a fairly predictable trend due to the development of AI. Especially since big data, cloud technologies, and other advancements are already significantly speeding up the accuracy of diagnostics. 

If you are considering custom development of medical image analysis software, now is the most favorable time. Below, we will reveal the specifics of creating such solutions and describe the requirements and the challenges you may face.

What is the definition of medical imaging software?

Medical imaging software—it's the digital tool doctors use to examine medical images. Think X-rays, MRI and CT scans, ultrasounds, PET, and other radiology scans. Basically, it helps to see the details of every complex illness and make informed decisions about patient care.

To maximize efficiency, medical imaging software integrates a range of advanced technologies. These include AI for anomaly detection, ML for image segmentation, and methods for filtering, contrast enhancement, and noise reduction to improve image quality. 

Also, 3D reconstruction technologies create volumetric models of organs and tissues. Developers also rely on the DICOM standard for medical images as it allows seamless transfer. They also use cloud tech to access data, integrated medical records, and VR and AR to visualize data and create interactive interfaces.

As a result, with medical image analysis software, healthcare organizations reduce the workload of their doctors and researchers and minimize the likelihood of misdiagnosis.

Examples of medical imaging software

To better grasp how these solutions work, we suggest you look at several medical imaging software examples that have gained worldwide recognition.

RadiAnt DICOM viewer

It is a high-performance medical imaging software that processes DICOM images. Due to its rich functionality, both doctors and researchers use it in their work. It has smart multimodality tools for 3D and 2D visualization and MPR (multiplanar reconstruction). Moreover, developers made the interface very user-friendly, so this software is also a great choice for users with low technical skills.

OsiriX MD

Specifically designed for macOS, OsiriX MD is a powerful DICOM platform that meets the needs of radiologists. Its advanced capabilities support 3D and 4D image analysis, hybrid imaging with PET-CT and PET-MRI, and integration with PACS servers. Crucially, it is FDA- and CE-certified for clinical us.

Horos

Horos is a free OsiriX-based DICOM viewer available on macOS. It has rich customization options for analyzing volumetric data, such as 3D reconstruction, and is especially useful for students and researchers. 

GE Healthcare Centricity PACS

GE Healthcare Centricity PACS is a proprietary enterprise medical image analysis software. It has EHR and EMR integration, real-time collaboration, advanced AI analysis, DICOM standards, and format support. It can be a full-fledged assistant for doctors and researchers. 

Philips IntelliSpace Portal

Tailored for large clinical institutions, Philips IntelliSpace Portal excels in medical image analysis and visualization. It integrates AI-driven automation and tools for multiparametric imaging in cardiology, neurology, and oncology; this medical imaging software supports multi-user collaboration.

Key features of medical image processing software

This section explores the key functionalities typically found in standard medical imaging software.

Tools for viewing and processing medical images

Ensure your medical imaging software works with various input data (CT scans, MRI scans, X-rays, ultrasounds, and hybrid studies like PET-CT and PET-MRI). Usually, this is done by supporting the DICOM format. In addition, you will need tools to scale, rotate, and adjust image contrast. So, optionally, develop a panel for 3D and 4D visualization, including multiplanar reconstruction.

AI-driven image analysis 

AI is key in automating the detection of anomalies in medical scans. It can identify cancerous tumors, blood clots, and fractures early, with a high degree of independence. Also, AI in your medical imaging software can classify pathologies using trained models. It can segment organs and tissues on scans and analyze multiparametric data.

Diagnostic and treatment planning tools

This includes tools for creating 3D models, surgical planning, and evaluating the effectiveness of treatment. You should also consider integrating your medical imaging software with robotic surgical systems.

Medical data management tools

To implement effective medical data management, you will probably need to integrate your medical imaging software with PACS (for storing and transmitting data), EHRs (for centralized access to personal patient information), and cloud solutions (for unimpeded access to images from anywhere in the world where there is an Internet connection).

Collaboration tools

It's mainly for remote access so doctors and specialists can chat and comment on each other's actions. It also involves integrating telemedicine platforms to discuss complex cases and hold educational seminars.

What development?

A wide range of organizations can benefit from medical image analysis software development. Now, let's find out which areas of healthcare benefit from medical imaging software the most.

• Cardiology.

In this field, medical imaging software is mostly used to analyze CT and MRI of the heart and angiography. In addition, it monitors treatment effectiveness, plans operations, and predicts cardiovascular disease risks.

• Dentistry.

Inevitable for 3D scanning when planning dental implants, diagnosing jaw diseases, visualizing root canals, etc.

• Oncology.
  Here, medical imaging software detects and classifies tumors, tracks their growth, and assesses treatment effectiveness.

• Neurology.

In this sector, medical image analysis software analyzes brain MRIs and CTs and provides 3D visualizations to assess the spine and nerves.

• Orthopedics.

Orthopedics studies thrive on precise X-ray analysis, which includes 3D joint modeling and spinal disease diagnostics.

• Mammology.

Medical imaging software can detect microcalcifications and early breast cancer through comparative analysis of changes in mammary gland tissue.

• Urology.

In this industry, medical imaging software helps diagnose kidney and bladder diseases. It does this by analyzing CT and ultrasound images. Additionally, the software can help plan operations and monitor patients with chronic diseases.

• Pulmonology.

Industry specialists can use such software to diagnose lung diseases, analyze chest CT data, and assess COVID-19 damage.

• Gynecology.

In most cases, medical image analysis software is used to perform pregnancy ultrasounds. It helps monitor the fetus, find pelvic tumors, and analyze the endometrium and other tissues.

• Traumatology and emergency medicine.

In traumatology, 3D medical imaging software can quickly diagnose fractures and internal injuries. It can also visualize organs for urgent decisions.

Still, deciding on the right healthcare sector for your medical imaging project? Contact us and discuss the possibilities of its practical implementation with Darly Solutions' experienced developers.

Medical imaging software development: Steps to follow

Custom development must follow clearly defined stages that most teams use. But, it can still be approached in various ways. Below, we outline how healthcare software development services are delivered in our company.

Concept formation 

Start your medical imaging software project with market analysis. Define the target audience, prioritize tasks the software should solve, and research competitors (to identify their strengths and weaknesses). Based on the insights, our medical imaging software development team assesses the functional requirements and evaluates the need for specific technologies to handle image processing. This ensures that the chosen solutions align with the project's technical needs and optimize the processing of healthcare-related images.

Planning

Once we agree on the conditions with all stakeholders, we will write a technical specification for your medical imaging software. This document will describe its functionality, interface, API, security, and integration requirements. We will also approve the tech stack and necessary integrations. Finally, we create a roadmap that defines the milestones and deliverables for each medical imaging software development project stage.

Prototyping

Now that everything is ready, we can begin creating user stories. They include handling DICOM file uploads and 3D models, among other key tasks. For UX/UI best practices of safe data, we follow the WCAG 2.1 guidelines. They ensure accessibility for users with varying technical skills. We also test prototypes with focus groups to see feedback on complex features, which is helpful for future design improvement. Finally, after the edits are done, we develop a full-fledged design.

Coding

The frontend has algorithms to process and analyze medical images. The backend ensures secure data transfer between the medical imaging software and storage. It also encrypts data and protects against vulnerabilities like SQL injections. These involve writing database queries for smooth software interactions and data storage interactions. And last but not least—we also integrate with your healthcare org's existing systems and services (if any).

Testing

Once the code for your medical imaging software is ready and all components have passed unit tests, we run complete test cases. We check for load, functional, non-functional, security, and usability issues.

Deployment

At this stage, we are choosing hosting for your medical imaging software (usually either cloud or local servers), setting up CI/CD, and training end users, for example, by providing them with documentation, training materials, or live courses. Once we've done it, we deploy the solution (first in the test environment and then—in the actual usage environment).

Support and updates

Finally, after the medical imaging software is deployed, we set up monitoring systems to track its performance and detect errors, fix post-release bugs, optimize it according to user feedback, and add new features if required.

Key tech specifications for medical imaging software development

Such software development can be complex, especially in its early stages. Basically, there is often no clear way to turn an abstract idea into actual requirements. 

So, let's examine all  the key tech specifications that are usually implemented in medical imaging software apps:

• Support for common medical image formats such as DICOM (including DICOM tags for metadata) and standards for storing, transmitting, and processing medical images (such as C-STORE, C-FIND, and C-MOVE).
• Compatibility with various devices (CT, MRI, ultrasound, etc.).
• Image processing can improve images by adjusting contrast brightness and applying filters. It can also segment them to highlight organs and tissues. Lastly, it can register them to compare scans over time.
• 2D and 3D visualization, including volume rendering (CT/MRI), support for iso-sections and reconstructions, and interactivity (e.g., rotation, zoom, and pan).
• Data security, including HIPAA and GDPR compliance, support for TLS (for data transfer) and AES-256 (for image and metadata storage) encryption standards, as well as access control with role-based authorization and two-factor authentication.
• PACS and EHR/EMR integration (e.g., via HL7/FHIR).
• Annotation (adding labels, arrows, and text comments) and providing real-time collaboration tools.
• PDF report generation and image export.
• Scalability (including horizontal scaling via the cloud), multi-threading, and hardware acceleration.
• WCAG 2.1 compliance and user interface customization.
• Logging and monitoring events (including loading, processing, and exporting scans), auditing user access, tracking system performance, and setting up failure notifications.
• Local deployment of software on physical servers (most likely, this will require ensuring compatibility with Linux and Windows OS).
• Setting up regular data backups and automatic recovery after system failures.

Of course, this is just a basic list of specifications. In practice, your project team will expand and refine the list of features while specifying the tools and technologies for the project's unique needs.

Medical imaging software development cost

When it comes to the development cost of medical image analysis software it depends on its complexity and the technologies used. Without data and business needs—it's hard to define the precise price, but on average, basic DICOM (Digital Imaging and Communications in Medicine) typically ranges from $30K to $300K. A customized version of Basic DICOM may cost $30K to $50K. Advanced customizations could cost $70K to $150K.

Implementation costs differ based on the size of the practice:

• Small practices typically cost $5K to $10K and take 1 to 2 weeks.
• Medium facilities cost $20K to $50K and take 1 to 3 months.
• Large enterprises may cost $100K to $200K and take 3 to 6 months.

Please complete this form to calculate the precise budget for your medical imaging software development idea. We will contact you shortly.

Challenges in medical imaging software development

Let's examine the main challenges encountered when developing medical imaging software.

• Regulatory compliance.
  Software handling sensitive data, like patient information, must comply with HIPAA, GDPR, FDA 21 CFR Part 11, and CE Marking regulations. Key security measures include code audits, RBAC, 2FA, and strong encryption (e.g., AES-256, TLS).
  To avoid fines, consult a local lawyer on medical standards.

• Integration with existing systems.
  Integrating PACS, EHRs, and other systems requires DICOM, HL7, and FHIR support. Also, medical organizations have very different established IT infrastructures, which makes it hard to unify their software. If you create a universal solution, you must provide some middleware. It will help users adapt to various services and systems.

• High performance and scalability.

Medical images, especially CT and MRI, are large. This can slow their processing and increase resource needs.
In this regard, you may need to implement lossless compression mechanisms for images and multithreading and parallel data processing algorithms. By the way, a common fix is to move your software to a cloud solution designed for healthcare businesses.

• The complexity of big data management.

Storing and processing massive data, like images and metadata, require a careful choice of databases and storage. In particular, this implies a preference for distributed databases and object storage.
For even greater reliability, do not forget to provide backup and auto-recovery.

• Risks associated with cyber attacks.

Cyber attacks that leak medical data are a serious problem for healthcare software. To solve it, you must implement constant monitoring. Also, set up regular security updates, including patches and OS updates.
Finally, train your staff on social engineering. It can reduce the risks of phishing attacks.
Providing a user-friendly interface.
Interfaces for doctors and medical personnel should be user-friendly and intuitive, requiring minimal technical training to operate efficiently. To achieve this goal, you must test hi-fi prototypes on the real target audience and perform subsequent optimizations. Also, do not forget to ensure your interface is created under the WCAG 2.1 guidelines.

The future of medical imaging software

Medical imaging software development will advance by adopting the newest technologies, process optimization, and increased integration with other medical systems. 

So, here are the core areas in which medical imaging software can be optimized:

• Speeding up diagnostic.
• Increasing image recognition accuracy.
• Costs reduction.
• Improving user experience.

This can be achieved through the implementation and development of the following technologies:

• Artificial intelligence and machine learning.

For highly accurate and automatic analysis of medical images and accelerated diagnostics.

• Cloud computing.

To provide quick access to medical images from anywhere in the world, process large amounts of data without the need to upgrade local infrastructure, and implement remote collaboration between healthcare specialists.

• VR/AR.

Medical imaging software development allows anatomy and pathologies to be studied using interactive 3D models and visualize the patient's anatomy before surgery.

• Quantum computing.

While most quantum computers are not yet available for widespread use, they will speed up processing large datasets and training neural networks for image recognition in a few years.

• Blockchain.

To guarantee the immutability and protection of data from medical imaging software while providing patients with comprehensive control over their medical information.

Our experience in medical imaging software development

This section covers the development of the PrismaORM brain scanner. This platform was crafted for chiropractors, neurologists, and neurosurgeons to monitor brain activity and brainwaves before, during, and after chiropractic treatments.

First, we assembled a team of eight experts to bring this vision to life. They worked closely with two external teams of medical imaging software engineers. We've pointed out a tech stack based on PostgreSQL, Typescript, React Native, Nest.js, Expo, Three.js, and SQLite. This tech of choice lets us build a platform that processes real-time data from brain activity helmets. The BLE protocol transmits this data. A tablet interface visualizes it. A key to the project's success was optimizing the user experience. This included better platform performance and integrating 3D models.

As a result—we've made a powerful tool that empowers medical professionals to conduct more precise diagnostics and offer more effective treatment recommendations. 

For a detailed look at this project, visit our portfolio.

Wrapping up

Now that you understand the specifics of medical image analysis software development, you can begin searching for a team to bring your project to life. We are a reliable provider of custom healthtech solutions, ensuring a smooth, transparent, and predictable collaboration. Simply fill out the form, and we'll get in touch as soon as possible to discuss your medical imaging software project in detail.

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Medical device software now drives the core of digital health. AI powers diagnostics, IoT connects patients to providers, and real-time data shifts care from reactive to predictive. According to recent statistics, the global SaMD market is projected to grow from $2.77 billion in 2024 to $52.87 billion by 2033 at a compound annual growth rate (CAGR) of 38.4%. The U.S. advances rapidly with FDA pathways designed for speed, while Europe maintains a GDPR-compliant digital health infrastructure, holding a 30% global market share.

Nevertheless, the future is bright for SaMD; it has benefits and challenges. Let's dive into the meaning of medical device software development, including the steps and types.

What Is Medical Device Software Development?

Medical device software development refers to designing, creating, testing, and maintaining software that is integral to the functionality of medical devices or operates as a standalone medical device. This software must meet strict regulations for safety and accuracy, including those from the FDA, MDR, and ISO 13485. 

Who Benefits from Medical Device Software Development

Demand for medical device software spans many sectors. Let's explore the industries leading the way.

Healthcare Providers

Real-time patient data helps providers make sharper decisions and diagnoses. Automation reduces manual errors and allows staff to focus on care. AI and IoT add efficiency and enable remote, personalized treatment. This delivers faster, safer care while cutting costs.

Medical Device Manufacturers

Medical device manufacturers use software to automate quality control and ensure compliance with regulations. Real-time monitoring reduces errors and helps make proactive adjustments. Scalable updates future-proof devices, while ERP systems improve supply chains, reduce costs, and accelerate time-to-market.

Pharmaceutical Companies

Pharma firms cut trial costs via wearables, automate drug production with digital batch records, and monetize AI-powered SaMD apps that improve adherence. Real-time monitoring speeds up approvals, while AI-driven data tailors therapies and unlocks revenue from digital treatments and SaaS models, sharpening efficiency and market edge.

Telemedicine Providers

Telemedicine thrives in video conferencing and remote monitoring, particularly in underserved areas. Yet, it needs specialized software to connect with medical devices for remote diagnosis, monitoring, and treatment. Modern medical device software improves access to care, diagnostic accuracy, patient engagement, and chronic disease management while also helping reduce hospital readmissions.

Biotech Companies

Biotech companies use medical device software to process complex biological data, speed up drug discovery, and perform diagnostics. Custom tools automate tasks while ensuring compliance with FDA and HIPAA regulations, reducing risk. The result? This tech drives innovation, cuts costs, and accelerates the development of market-ready biotech products.

Clinical Research Organizations (CROs)

CROs gain efficiency and accuracy through automated data handling in device trials. Better data management and real-time monitoring improve trial quality and speed. This leads to faster market entry, reduced costs, and ensured regulatory compliance.

Research and Development Laboratories

Medical device software transforms R&D labs. Thus, teams automate tasks, use AI for sharper data analysis, and lock in compliance from day one. As a result, labs hit faster diagnostics, therapies, and disease control breakthroughs without slowdowns.

Advantages of Software Development for Medical Devices

Software is the new heartbeat of healthcare, making devices smarter, faster, and more efficient. Better outcomes and lower costs are just the beginning. Discover the full positive impact below.

Increased diagnostic accuracy

Medical device software improves diagnostic precision through advanced data analysis techniques. Algorithms detect subtle patterns humans might miss, especially in imaging and laboratory results. Machine learning models continually refine their accuracy by analyzing millions of patient cases, significantly reducing error rates.

In practice, whole-slide imaging in digital pathology achieves a diagnostic concordance of 96.5%, matching that of traditional light microscopy. AI models like GPT-4 show pooled diagnostic accuracy of 52.1%, on par with non-expert physicians but still below experts by 15.8%

Process automation

Automation eliminates repetitive tasks, reduces errors, and allows medical staff to focus on patients. The software handles everything from scheduling to medication management, reducing costs while boosting efficiency. Hospitals report significant time savings and happier staff after implementing automated systems.

Real-time patient monitoring

Connected devices track vital signs without constant staff presence. The software alerts doctors when readings breach safe thresholds for immediate intervention. This capability saves lives in ICUs and helps patients with unpredictable chronic conditions.

Integration with medical systems

Medical software integrates with hospital databases, electronic health records, and laboratory systems. This eliminates data silos and ensures all providers see complete patient information. System interoperability reduces duplicate data entry and lowers the risk of transcription errors.

For instance, integrated medical software reduces duplicate data entry by 30% and transcription errors by over 50%. Hospitals with connected EHR and lab systems report a 25% boost in care coordination and faster clinical decisions.

Regulatory compliance

Built-in audit trails, access controls, and encryption protect patient data while meeting legal medical device software standards. These safeguards prevent costly violations and data breaches that damage trust and finances.

Flexibility and scalability

Medical software adapts to changing needs through modular design and cloud deployment. Solutions scale from single clinics to hospital networks without performance loss. Providers start with core functions and expand as requirements evolve.

Remote access and telemedicine

Telemedicine breaks geographical barriers to healthcare delivery. Remote monitoring enables home recovery while maintaining professional oversight. These systems maintain care continuity during emergencies when facilities reach capacity.

Cost reduction

Software-driven automation delivers significant savings through improved efficiency. Predictive maintenance prevents equipment failures and reduces downtime. Digital transformation reduces administrative overhead, with hospitals reporting a 30% decrease in operational costs. 

Improved user experience

Intuitive interfaces cut training needs and boost adoption among medical staff. Human-centered medical device software design makes complex technology accessible to everyone. Patient apps improve treatment adherence with simple instructions and timely reminders.

Support for analytics and AI

Analytics transform medical data into actionable insights for treatment. AI identifies high-risk patients before acute episodes occur. Machine learning models continually improve with new clinical data, keeping recommendations updated with medical advances.

Key Aspects to Consider in Medical Device Software Development

Medical device software revolutionizes healthcare, but building it is no walk in the park. From regulations and compatibility to testing and ongoing maintenance, the stakes are high, and the margin for error is zero in medical device software development. Here's what matters most and saves lives.

Meeting Regulatory Standards

Regulatory compliance is non-negotiable. Developers must navigate a maze of standards from bodies like the FDA or EMA, which classify software based on risk and dictate the approval process. Whether it's a 510(k) or a PMA, getting them wrong can result in costly delays or outright rejection. Stay updated, plan for compliance from day one, and document everything—regulators love paperwork.

Ensuring Data Security and Privacy

Medical software handles sensitive patient data, which makes security a top priority. Encryption, secure authentication, and regular audits are must-haves to protect against breaches. HIPAA and GDPR aren't just guidelines—they're the law. One misstep can lead to hefty fines and a PR nightmare, so lock it down.

Designing for Usability and User-Centered Experience

If your software design for medical devices isn't user-friendly, it's a liability. Engage with doctors, nurses, or patients early and often to design interfaces that reduce errors and fit seamlessly into their workflows. Accessibility isn't optional—it's essential. A confusing UI can lead to misdiagnoses or delays, so make it intuitive and easy to use.

Ensuring Compatibility with Healthcare Systems

The software never lives in a vacuum. It must comply with EHRs, LIS, or PACS, using standards like HL7 or DICOM. Since interoperability isn't just a buzzword—it's how data flows smoothly in healthcare—build with flexibility in mind. Systems change, and your software should keep up.

Implementing Effective Risk Mitigation

Risk management is baked into medical software development. Use frameworks like ISO 14971 to identify hazards, assess risks, and implement controls to manage them. Plus, tools like FMEA help catch issues before they become disasters. In this field, an ounce of prevention is worth a pound of cure.

Thorough Testing and Quality Validation

From unit tests to clinical validation, every layer counts. Rigorous validation, covering unit, integration, system, and user acceptance testing, helps catch defects early. Include performance, security, and interoperability checks. Pay attention to documenting everything: regulators will demand proof.

Ongoing Maintenance and Software Enhancement

Launch day is just the beginning. Bugs, security patches, and new features require constant attention. Set up a robust post-market surveillance plan to catch issues early. Your software should evolve with healthcare, not fall behind.

Types of Medical Device Software

Based on hardware and regulatory integration, medical device software falls into two primary categories:

Embedded Software for Medical Systems (EMSSW)

This type of software is an integral part of medical devices, such as pacemakers, infusion pumps, and imaging machines. Embedded systems control device functions, ensuring they operate safely and effectively. It is not standalone software like desktop or mobile apps, and it cannot function without the hardware of the medical device.

Examples of Embedded Software for Medical Systems (EMSSW) are:

• Pulse oximeters.
• Smart bio-sensors.
• Glucometers.
• Electronic blood pressure sensors.
• Medical imaging devices, such as X-rays, MRIs, and CT scans.

Standalone Software as a Medical Device (SaMD)

Standalone Software as a Medical Device (SaMD) performs a medical function independently of dedicated hardware. Think algorithms spotting heart issues in ECGs or apps managing diabetes. Regulated by the FDA and EU MDR, it operates on phones, laptops, or clouds, slashing costs and supercharging care delivery.

Examples of Standalone Software as a Medical Device (SaMD):

• Patient imaging or scan analysis.
• Remote ECG-monitoring.
• MRI Viewing applications.

Steps in Medical Device Software Development

When lives depend on technology, there's no room for error. Follow the steps of medical device software development grounded in timeless principles: safety, usability, and trust.

Comprehend Regulatory Standards

Compliance encompasses global frameworks such as IEC 62304 (software lifecycle management) and ISO 13485 (quality management), as well as regional mandates, including FDA design controls in the U.S. and MDR/IVDR in the EU. Data privacy laws, such as HIPAA in the U.S. and GDPR in the EU, govern the handling of patient information. Developers must integrate these standards early, ensuring risk management, usability testing, and documentation meet audit requirements. A deep understanding of these rules prevents costly delays and ensures software reliability in clinical settings.

Conduct Market Research and Identify User Needs

Research market trends and competitors to define your software's unique value. To gather user needs, engage stakeholders, such as clinicians, patients, and administrators, through interviews or surveys. Translate these into clear use cases and functional requirements aligned with clinical workflows. 

Select an Experienced Development Partner

Choose a development partner with proven expertise in medical device software and IEC 62304 compliance. Ensure they understand relevant regulations, such as FDA or EU MDR, and can support submissions and audits. Verify their technical skills in areas such as embedded systems or AI, and confirm that they follow rigorous testing protocols. Prioritize clear communication and strong project management to meet your timeline and goals.

Development and System Integration

Adopt an iterative development approach, such as Agile, tailored to IEC 62304 to balance flexibility and traceability. Design a modular software architecture for scalability and integration with hardware or external systems, such as EHRs, using standards like HL7 or FHIR. Follow secure coding practices and document code for compliance. Integrate software with hardware or APIs, then conduct thorough verification and validation through unit, integration, and system testing to ensure safety and performance.

Deployment and Ongoing Monitoring

Prepare regulatory submissions, such as a 510(k) for the FDA or a Technical File for EU MDR, to gain market approval. Deploy the software in phases, starting with pilot testing in clinical settings to validate real-world performance, train users to ensure proper operation, and minimize errors. Implement post-market surveillance per ISO 13485 to monitor performance, collect feedback, and address adverse events. Use analytics to track usage and identify issues, such as cybersecurity threats.

Ongoing Support and Maintenance

Provide prompt bug fixes and updates to enhance functionality or security, ensuring compliance with regulations for significant changes. Offer user support through helpdesks or chatbots to resolve issues. Plan periodic upgrades to keep up with new clinical needs and technologies. Prepare for software end-of-life by managing data migration and complying with data retention rules.

How to Select the Best Medical Device Software Development Company for Your Project?

First, clearly define your project goals and requirements. List specific features like AI diagnostics or cloud integration, compliance needs (e.g., FDA, EU MDR), and budget constraints. Identify the target users, such as clinicians or patients, to guide usability expectations. This ensures you communicate precise needs to potential vendors.

Second, research companies with a proven track record in medical device software. Check portfolios for projects like remote monitoring or EHR-integrated tools. Review client feedback on platforms like Clutch or KLAS Research. Confirm their experience with regulatory approvals, such as ISO 13485 or CE marking.

Third, evaluate their regulatory expertise. Ask how they handle standards like HIPAA, IEC 62304, or FDA guidelines. Request examples of compliance documentation or successful submissions. Strong regulatory knowledge prevents delays and costly revisions.

Fourth, assess their technical capabilities. Verify expertise in your required tech stack, such as IoT, HL7/FHIR for interoperability, or secure cloud platforms like AWS. Ensure they can integrate with healthcare systems and support cross-platform development. Technical alignment reduces risks and boosts performance.

Fifth, prioritize cybersecurity expertise. Confirm they follow secure medical device software engineering practices like OWASP's S-SDLC and use encryption and authentication. Ask about their process for regular updates and vulnerability patches. Robust security protects patient data and builds trust.

Sixth, check their focus on user-centric design. Review examples of intuitive, compliant interfaces for medical devices. Ensure they conduct UX research to minimize user errors. A user-friendly design improves adoption and care outcomes.

Seventh, confirm their collaboration and transparency. Look for clear communication, detailed project plans, and methodologies such as Agile or Scrum. Request clarity on pricing, timelines, and milestones. Transparent collaboration aligns the project with your vision.

Eighth, compare costs while prioritizing value. Expect custom medical software to cost between $ 200,000 and $400,000, depending on its complexity. Ensure they offer scalable solutions and ongoing support. Choose a vendor that strikes a balance between quality and budget without compromising on standards.

Finally, shortlist 3-5 companies and request detailed proposals from them. Conduct interviews to assess their approach, certifications, and alignment with your goals. Select the partner with the best mix of expertise, reliability, and transparency. Sign a contract only after reviewing terms and ensuring mutual clarity.

The Future of Medical Device Software Development

Medical device software already stands at the cutting edge of healthcare innovation, driving massive change in how we diagnose and treat patients. Yet, with billions of dollars flowing into health tech and regulatory barriers easing, the future of medical device software development is bright for the coming years. 

AI and Machine Learning Integration

AI algorithms are already making waves in the medical device software sector. Predictive analytics and personalized treatments help spot patterns humans miss, delivering faster diagnoses and better outcomes. The tech now works across nearly every medical specialty, and the trends show it won't stop soon, only evolve.

Cybersecurity as Priority

Security doesn't leave the center stage as connected medical devices face sophisticated threats. Manufacturers now build in encryption, strong authentication, and continuous security monitoring from day one. Patient data protection matters as much as clinical functionality.

Edge Computing Implementation

Processing moves to the device itself, shortening wait times for essential procedures. The tech works even when networks fail, and it is a game-changer for implantables and wearables. Edge computing delivers real-time insights exactly when patients need them.

Interoperability Standards

The industry finally tackles its fragmentation problem with standards that work. FHIR and open APIs create true connectivity between previously siloed systems. The seamless data flow means better decisions based on complete patient records.

Sustainability and Scalability

Developers focus on energy-efficient software to extend the battery life of devices. Modular designs allow easy updates without replacing hardware. Cloud integration supports scaling for large patient populations. This reduces costs and environmental impact.

Regulatory Evolution

Regulators are finally catching up to tech innovation with more flexible frameworks. The FDA and international bodies now offer pre-certification pathways and real-world performance monitoring. Companies can innovate faster while still proving their products are safe.

Why Darly Solutions is Your Best Medical Device Software Partner?

No cookie-cutter code here. We're healthcare tech experts who solve real problems. For hospitals, clinics, and MedTech startups, we've delivered over 60 projects that handle messy data, strict compliance, and seamless integration.

Every solution is tailored, whether you're upgrading old systems or launching new ones. Our tech stack is healthcare-tested: secure, compliant, and built to last. Here's how we do it:

Our services cover:

• Custom software development for unique workflows.
• App development that works across devices.
• Cross-platform solutions to reach more patients.
• Automation services to slash admin time.
• UI/UX design that the medical staff actually uses.
• Integration services to connect legacy systems.

We build dashboards that act, not just display. Our scheduling tools cut admin work in half while keeping patients happy. Need e-prescribing or billing that's both secure and fast? We've done it reliably on a large scale.

Need experts who speak healthcare? Whether it's a whole managed IT team or project-specific help, we're here. Outsource your software development to us, and let's build tools that save time, money, and lives.

Conclusion

Medical device software development is more than code—it's about building tools that make healthcare smarter, safer, and faster. With the right partner, you get solutions that boost outcomes, cut costs, and keep you ahead of the curve. Darly Solutions brings deep healthcare expertise, proven results, and a relentless focus on real-world impact. If you're ready to transform your healthcare business, Darly Solutions is the team to trust.