Applications of AI and ML in 2021 mHealth
To understand the role of AI and ML in healthcare, let’s explore the benefits and the functionality of these two technologies in the healthcare industry.
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The healthcare industry has undergone a significant transformation in the past few years. The expansion and influence of machine learning and artificial intelligence have given a rise to a new ecosystem. Still, most times, those two technologies are described as a magic wand that has come to change the system.
The Rise of Health Mobile Apps: A Market Overview
Mobile health (shortly mHealth) refers to public health and medicine delivery services through mobile devices. With digitalization gradually covering all the segments, the healthcare industry has registered significant growth in mobile apps.
The smartphone penetration soon brought to the mHealth apps’ market growth. It has registered $40.05 billion in 2020 and is predicted to grow at a CAGR of 17.7% from 2021 to 2030. The segment of mobile health already counts over 31.000 health-related apps for both patients and the medical centers. And, the number is growing every day.
As a vast field, mobile health offers business and investment opportunities. Still, the segment lacks technologies and new business models. The present-day overview registers great market potential in the US, UK and Germany, Canada, Israel, the Netherlands, and Denmark. With the attractive market size, mHealth will soon become an ecosystem. It will deliver digital solutions and improve the quality of life.
Mobile Healthcare and Technologies
Mhealth apps like medicine delivery or telemedicine are all aimed at making medical services faster. This very responsible segment and mobile technologies are already registering beneficial changes.
EMS (Emergency Medical Service) Data Collection
The traditional workflow of medical institutions with tons of paperwork was the first thing to improve. The digitalization of data collection and storage enabled real-time data access. It contributed to no-delay performance in creating immediate reports.
EHR (Electronic Health Record) Practices for Reducing Paperwork
By digitalizing the records, it is possible to direct time and effort to serve patients. EHR is the top technology that delivers changes. The service is also integrated with health mobile apps and medicine delivery apps to register patient data even out of the hospital. The technology is controlled by HIPPA (Health Insurance Portability and Accountability Act). The organization ensures patient’s electronic data privacy for implementing digital technologies.
Timely Medications With Medicine Rate App and Medicine Delivery App
Digital medical system creates patient experience both inside the hospital walls and at home. Medicine-related apps like medicine delivery are more than delivery app. It saves patients' history, e-prescriptions, online payment bills, etc.
Health Trackers and Wearables
The top innovation gadgets trending around are more than fun. FDA-approved health trackers are now generating real-time data. The algorithm fixes any single change and alarms possible danger. Mass-market wearables are used to track personal wellness. Related mobile apps support and process collected data and transmit it to the backend server. This non-stop process creates reports for periods and helps the users to track the changes.
What Technologies Are Used in Mobile Healthcare?
Healthcare, which is already smart, is now driving higher efficiency with apps and IoT. The wearables, smartwatches, health devices, and fitness trackers are IoT devices. They all provide continuous data collection and synchronization with mobile apps. The technology can now send a patient’s data to a doctor without his physical presence and get on with further treatment.
Most of the mHealth functionality is driven by AI and ML. Those two top technologies guarantee the future of healthcare.
Statistics of AI and ML Applications in Mobile Healthcare for 2022-2030
The impact of AI/ML game-changing technologies on mobile healthcare has brought significant market growth. The market is predicted to register over $35.892 million by 2030. In 2021, it has already registered $6.6 billion.
- 80% of mobile technologies used for healthcare mobile apps will be based on AI.
- By 2025, AI and ML will replace 16% of US jobs.
- The market of AI-based wearables will generate $180 billion by 2025.
- By 2030, China will have the largest share of the AI global market (26%).
- AI applications will create $150 billion in savings for US healthcare.
Artificial Intelligence in the mHealth Industry
Artificial intelligence has the highest potential in the automation of processes in healthcare. The healthcare industry that will soon have a shortfall of 9.9 million physicians, needs automation. AI, defined as the capability of a computer program to fulfill tasks, is usually associated with human intelligence. This mobile technology presents a set of algorithms enabling devices to sense, collect data and make predictions.
AI Use Cases in the Healthcare Industry
At present, there are dozens of artificial intelligence use cases in mobile healthcare that make apps more functional:
- Automated diagnosis & prescription. The technology enables chatbots that assist both patients and doctors. AI-based chatbots may give an initial diagnosis or prescription to the patient. The answer will be based on the symptoms before he/she will be able to talk to a doctor.
- Prescription auditing. Prescription errors are now automated and saved in one place through an AI audit system. This technology is used in medicine rate apps.
- Real-time prioritization. AI-based perspective analytics on patient data enables precise case prioritization and triage.
- Personalized care and medications. AI processes patient data and generates the best treatment plan. As a result, the technology increases care effectiveness.
- Data Analytics. The first implementation practice of artificial intelligence was data analytics. The technology facilitates the processes of saving clinical data, discovering insights, and suggesting actions.
- Customer service chatbots. With AI, customer service works more effectively. It will give instant answers about medicine delivery, appointments, bill payments, etc.
- Creating new roles. With the new ecosystem of mHealth and AI, the industry will need new talents to handle the technology. To support the technology, data engineers and app developers will be in great demand.
Machine Learning in the Healthcare Industry
The biggest technological breakthrough of the healthcare industry is the implementation of ML. The technologies digitize healthcare for the smartphone-centric generation.
The technology is aimed at building autonomous and intelligent devices capable of operating without human interaction. Machine learning works on a set of algorithms that supports the processes of AI. The latter, in its turn, enables machines to function independently.
ML Use Cases in the Healthcare Industry
Machine learning, supported by AI technologies, is already implemented in mobile healthcare. Machine learning copies the functions of human brains. Later it uses neural networks to detect the changes that the human cannot see. Here are some examples:
- Drug discovery. One of the first successful implementations of ML is precision medicine. It is a new method of sequencing to ensure drugs have the right effect on the patient.
- Personalized treatment. Just like the way each body reacts to food differently, it reacts to treatment and drugs. For some, the treatment may be effective, and for others, it may be useless or even dangerous. ML will help to generate personalized treatment based on a patient's medical history. Real-time data monitoring will align treatment depending on abnormalities.
- Adjusting behavior. Through machine learning, it is possible to fix daily activities. The supporting app alerts activity that might be dangerous for health from the long-term perspective.
- Health records improvement. The basic and top priority outcome of ML is keeping health records. The technology classifies data through OCR recognition techniques.
- Behavioral modification. One of the newest practices of implementing ML technology is behavioral monitoring of patients. It reveals lifestyle and behavioral changes important for a healthy body and mind. Such solutions are mobile apps and wearables with supported apps.
Both ML and AI will take the industry a big step forward to new generation healthcare. Dealing with challenges like security, data storage, accuracy can be achieved progressively. As a developer, think about creating a life-changing healthcare app to meet the industry's needs.
- Matching app with healthcare standards. Keep the standards to maintain privacy and functionality and become a trustworthy product.
- Planning design. Intuitive and interactive design is the main point of driving value with health apps.
- Integration with other platforms. The ability to integrate with existing software is the main factor in getting application recognition.
The healthcare space, with potential, will soon become the most expensive infrastructure. With advanced skills and knowledge, it is possible to be a part of the global healthcare market.
Published at DZone with permission of Anahit Ghazaryan. See the original article here.
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