How AI in Healthcare App Development Transforms The Future of Medicine
Artificial Intelligence (AI), a powerful technology, is changing the world as we know it by making it ‘smart.’ From improving our decision-making capabilities to how we interact or consume information, AI is transforming the reality of many industry sectors, including healthcare.
AI adoption in healthcare impacts and reshapes how we perform diagnoses, treatments, and medical care. It enhances workflows and operations, automate repetitive tasks, resolve patient query faster, and provide personalized treatment plans and therapies. Hence, AI in healthcare app development is profitable, as it benefits patients, researchers, clinicians, and healthcare professionals.
Moreover, AI in the global healthcare market is expected to grow at a CAGR of 37% from the period of 2022 to 2030, reaching $188 billion by 2030. As a result, AI is proving to be a futuristic technology with the potential to improve disease diagnosis, reduce healthcare costs, and revolutionize treatment plans and prevention.
So, how is AI used in healthcare app development? Let’s understand!
What is the Role of AI in Healthcare App Development?
AI in healthcare analyzes a large volume of stored data (images, clinical research trials, medical claims, etc.) to identify patterns and insights, exceeding human capabilities. It enables you to diagnose, treat, or prevent disease with enhanced accuracy.
The AI algorithms select, refine, convert, train, and process data to make predictions or classifications, helping healthcare professionals improve their treatments and reduce costs. Moreover, the data science behind ML keeps the model’s performance check for its effectiveness with proper evaluation and continuous improvement.
Categories of AI Applications in Healthcare
From analyzing patient records and medical imaging to discovering new therapies, AI is already changing the various aspects of healthcare.
AI supports various stakeholders in healthcare, and its applications can be divided into 3 broad categories:
Artificial Intelligence in healthcare applications surrounding patient care and outcomes falls under this category. These healthcare AI apps benefit patients from health monitoring and personalized treatment plans to engagement.
There are many types of patient-centric healthcare apps exist, such as:
The next category of apps that use AI in the medical field encompasses the needs and challenges of medical professionals like doctors, clinicians, nurses, and specialists. These apps help them in intelligent decision-making and streamline clinical workflows, improving healthcare service delivery efficiency and quality.
Many types of apps can assist healthcare professionals in their work.
Radiology and Medical Imaging
Pathology Assistance Apps
Clinical Trials Matching Apps
Electronic Health Record (EHR) Enhancement Apps
Radiation Therapy Planning
In healthcare organizations, a large amount of operational and administrative work needs to be done and managed efficiently. It includes managing financial processes, data, billing, appointments, resource allocation, etc. Applications of AI in healthcare automate these operational tasks, making medical practices more aligned and cost-effective.
Healthcare Data and Resource Management
Billing and Revenue Cycle Management
Claims Processing and Denial Management
Patient Admission and Discharge Planning
Smart Appointment Scheduling Management
Revenue Cycle Management and Budgeting Applications
Risk Assessment and Fraud Detection
Types of AI Technologies in Healthcare App Development
AI uses in healthcare and related technologies are becoming more prevalent than ever. It is transforming many aspects, including guiding researchers, streamlining administrative processes, and improving patient care.
Let’s look at the types of AI technology in healthcare app development.
Machine Learning and Deep Learning
Machine learning is the most talked about technology of AI that deals with training models with data. Deep learning and neural networks (subfields of machine learning) are the two complex aspects of ML used for healthcare research and predicting outcomes.
The common ML practice in healthcare apps is training datasets likely to succeed for medical precision, i.e., indicating treatment plans and plans.
Natural Language Processing (NLP)
With speech recognition, text analysis, and translation, NLP understands the human language or information gathered in formats other than numerical. Healthcare apps use NLP to comprehend and classify clinical documentation and research information for notes and reports and assist customers with conversational AI.
This subfield of ML and AI in healthcare discovers patterns and correlations in data to predict future outcomes. In healthcare, doctors, clinicians, or professionals use this technology to identify treatment plans based on the symptoms.
Moreover, it can determine when the clinics or hospitals are largely crowded to report forthcoming check-ins to optimize appointment scheduling and better staff placement.
Robotic process automation (RPA) uses computer programs on servers following scripts/rules to automate workflow, making the system intelligent. Healthcare apps use RPA to automate routine administrative processes like billing, updating patient records, or authorization, increasing operational efficiency and productivity.
In AI, speech recognition is used to process human speech into a written format, eliminating the need for manual data entry. The AI healthcare application enables conversational AI to reduce paperwork and human error, saving time and effort.
Rule-based Expert System
These are the standard ‘if-then’ rules-based practices followed in healthcare to carry out clinical decision-making. This system required human expertise and a set of rules for its creation. However, due to being time-consuming and having a probability of rule-confliction, this method is replaced by better ML practices and algorithms.
Top Use Cases of AI in Healthcare App Development
It is estimated that $265 billion worth of care services will shift from traditional facilities to homes by 2025, accounting for fast and convenient medical care facilities. This has all been possible due to technological advancement in the healthcare sector by the next-gen healthcare app development company.
Healthcare and artificial intelligence support various medical practices, ensuring faster processes, fulfilling workforce needs, improving patient satisfaction, and reducing costs. There are many uses of AI in healthcare app development, such as:
Medical Imaging Analysis
With medical imaging analysis, AI apps allow healthcare professionals like radiologists or cardiologists to review MRIs, X-rays, and scans in an accurate and timely manner. This empowers them to detect anomalies, diseases, and abnormalities, avoiding any errors in the reading and providing more precise diagnoses.
Healthcare apps collect patients’ electronic health records (EHR) to optimize their cancer treatments through radiation therapy. AI detects the old records to enable healthcare practitioners to make an informed decision regarding the radiation dose, protecting the healthy cells and improving the safety and effectiveness of radiation therapy.
One of the advanced uses of AI technology in healthcare is to discover and develop medicine for genetic disorders. It studies genomic datasets and predicts any alterations that can lead to illness, allowing healthcare service providers to customize their treatment plans.
AI is being used in healthcare app development to enhance patient participation in adopting advanced healthcare solutions and making smart decisions about their health. The features like reminders, personalized health information, and customized content improve patient satisfaction.
Administrative AI healthcare applications automate the recurring operational tasks of hospitals, clinics, or other healthcare facilities. This includes resource allocation, appointment scheduling as per doctor’s availability, billing, managing patient records, etc.
Diabetic Retinopathy Screening
With the help of AI, healthcare apps can act as a low-cost diabetic retinopathy detection tool, assisting in the early prevention of vision loss in diabetic patients. It analyzes retinal images to detect more-than-mild diabetic retinopathy (mtmDR), simply put, the early signs of diabetic eye disease.
With AI and ML capabilities, healthcare practitioners can analyze medical imaging, reports, etc., to help them identify abnormalities found in the test. This allows doctors to provide diagnoses with utmost accuracy.
AI-driven Drug Discovery
This AI-driven platform combines the power of biology, data science, and chemistry to process the traces of drugs, identifying their mechanism and toxicity. This revolutionary application shows remarkable precision in reimagining pharmaceutical innovation.
Virtual Assistants and AI Chatbots
One of the most common uses of artificial intelligence in healthcare examples includes developing or integrating virtual assistants or AI-powered chatbots in applications. With conversational AI, this function allows patients to schedule appointments or ask healthcare-related queries, whereas healthcare service providers can update doctors’ availability and medical information quickly. Hence, it makes life easy for both patients and healthcare service providers.
Automation and Ambient Clinical Intelligence
With automatic speech recognition (ASR), natural language processing (NLP), and deep neural networks (DNN), AI healthcare apps process the patient’s audio from the virtual interaction to generate clinical notes and improve system transparency and decision-making. Moreover, it automates clinical workflow and repetitive tasks, leading to more effective patient care.
How Artificial Intelligence Benefits Healthcare App Development?
With artificial intelligence in healthcare apps, medical professionals align their workflow process, provide quality patient care, maintain budget efficiency, and reduce human error. The potential of AI in healthcare is reshaping the way healthcare providers deliver care.
AI in healthcare apps has made collecting and sharing information easy and fast, facilitating better analysis and data-driven insights on treatments.
Artificial intelligence healthcare applications process a vast amount of data, helping doctors and care providers to analyze diseases, risks, and treatment plans with better accuracy.
Remote Healthcare Facilities
It revolutionizes the way remote healthcare facilities reach people with the convenience of smartphones. Faster and effective appointment scheduling ensures healthcare facilities set foot everywhere, including in rural areas.
As health and fitness problems are becoming more prevalent, monitoring your vital signs, day-to-day activities, and diet is essential. During checkups, patients can provide accurate information to their doctor so that any disease that might occur can be detected early.
Automated Administrative Processes
Applications of AI in healthcare automate administrative workflow, including mundane tasks, leads to better efficiency for hospitals and other medical care providers.
Enhanced Patient Experience
By integrating AI capabilities into healthcare apps, patients can receive personalized care, resulting in a better overall experience.
The effortless data processing in AI healthcare apps can help with the early detection and prevention of diseases, ensuring cost-effective solutions for people.
With a focus on human interaction in medicine, we build powerful AI healthcare applications that exceed your expectations. Here is the step-by-step process of building an intuitive healthcare application powered by AI.
Design and Develop AI Solutions
Combining the power of technical, strategic, and operational expertise, we ensure user-designed research to identify milestones, challenges, and success metrics. After considering the existing norms and problems, we contextualize algorithms that offer suitable outcomes to end-users.
Evaluate and Validate the Predictions
The next process is to assess the predictions made by the system to check what works and what doesn’t. We evaluate the system’s robustness with accuracy, stability, real-time performance in a dynamic environment, and investment benefit relative to cost.
Scale-up AI Systems
This phase includes updating the model to adapt and accommodate increased data volumes and users. With the scaling up of AI systems, we maximize its impact to ensure they continue delivering value across a broader user base.
Monitor and Maintain
Lastly, the final step involves continuously monitoring and maintaining the AI systems to ensure their sustained performance, reliability, and relevance. We monitor and address the system’s performance and issues in real-world scenarios as they arise. Also, update AI algorithms for regular maintenance and responsiveness to develop an AI healthcare application that remains effective and provides lasting value.
Key Considerations and Challenges to Building a Reliable AI-driven Healthcare App
The use of AI in clinical practice remains limited and faces many challenges despite significant progress in recent years. Therefore, you must consider many factors while developing your human-centered AI healthcare application, including clinical workflows, user needs, trust, safety, and ethical implications.
Data Privacy and Security
Ensuring robust data privacy and security in AI-driven healthcare applications is essential to safeguard patient information and facilitate secure data transmission.
Regulatory Compliance (HIPAA, GDPR, etc.)
There are various healthcare compliances, like HIPAA, HITRUST, GDPR, etc., that you need to follow to ensure your application adheres to legal and ethical standards.
Ethical and responsible practices, in addition to safety and regulation, are one of the widely encountered challenges in AI-driven healthcare applications. Therefore, you must hire a reliable healthcare app development company that addresses these issues and implements transparency in decision-making.
Integration with Existing Healthcare Systems
In some cases, a healthcare system may already exists, and AI technology must be integrated to enhance its capabilities and performance. Therefore, integration capabilities of AI-enabled healthcare apps with existing healthcare systems is critical to ensure interoperability and data exchange.
Accuracy and Reliability of AI Models
The next challenge is generating accurate and reliable outcomes from the AI healthcare application. As a result, AI models must be rigorously trained and validated to enhance results and minimize errors or incorrect recommendations.
AI in Healthcare: What the Future Holds?
Despite the high-level research on the application of AI in healthcare app development, there is so much potential in this field that is yet to be explored. Let’s understand how healthcare apps will be transformed with AI potential in the coming years.
The introduction of AI in healthcare app development enables healthcare professionals to make highly accurate and personalized diagnoses and treatment recommendations. The future of healthcare promises more effective treatments and improved patient outcomes with a remarkable enhancement in medical precision.
In the coming years, AI will revolutionize the drug discovery process, accelerating the development of new drugs. Hence, more and more healthcare businesses will potentially find breakthroughs in treating various diseases and conditions.
Wearables and Sensors
In the future, AI healthcare applications will rely more on wearables and sensor integration to monitor vital signs, activity levels, and various health metrics. AI algorithms will analyze the data in real time, enabling early detection of risks and warning signs and allowing people to receive timely clinical assistance.
Reduce Cost and Complexities
AI-driven solutions are expected to reduce the cost and complexities associated with healthcare delivery. In addition to accurate diagnoses and personalized treatments, AI applications will meticulously optimize and streamline healthcare practices, removing the intricacies and making them more cost-effective.
Transformative AI Healthcare App Journey With Successive Digital
Successive Digital created an advanced AI healthcare web platform to modernize patient care and communication with patients and the community. We deliver a seamless and intuitive user experience and patient outcomes by leveraging industry-leading AI solutions.
Resolving challenges like complex code base, prolonged response times, and lack of automation, we transformed this comprehensive healthcare solution with scalability and reliability.
We developed an AI-enabled, digitized healthcare platform that generated exceptional results.
Improved Customer Experience: 90%
Reduced Cost: 35%
Successive Digital Elevates AI Experience in Healthcare App Development
With our customer-centric healthcare app development services, we develop robust healthcare app solutions powered by AI technology. Our developed healthcare mobile apps adhere to industry regulations like HIPAA, prioritizing the security and privacy of patient data.
As a reliable healthcare app development company, we ensure uninterrupted support to intensify your app’s performance and provide a seamless user experience. Our healthcare experts thoroughly audit your app to deliver optimal performance of your app.
Want to leverage our all-in-one solution for all your healthcare app development needs? Contact us today!
FAQs for AI Applications in Healthcare
The cost of developing a healthcare app will depend on the type of healthcare app you choose to build. There are many other factors that you need to consider for estimating the mobile app development cost of an AI healthcare app, such as platforms, complexities, functionalities, etc.
Based on various cost-driving factors, an AI-based healthcare app costs $60,000 to $300,000 (or more). However, this cost may vary depending on your requirements.
The time to build an AI-driven healthcare app will depend on the project’s scope and complexity. For example, a simple app can take 200 to 600 hours, whereas a high-complexity app will require 650 to 1200 hours (or more).
There are a range of different AI technologies used in building a powerful AI application, such as Machine Learning (ML), Natural Language Processing (NLP), Computer Vision, Deep Learning, Predictive Analytics, Robotic Process Automation (RPA), etc.