The Role of Artificial Intelligence in Healthcare Sector 2021
What is the role of AI in the healthcare industry?
The role of Artificial Intelligence (AI) in healthcare delivers advanced and precise healthcare services. AI and Machine Learning (ML) technologies offer thrilling opportunities for the healthcare sector. From molecular research and development functions to clinical decisions, everything is performed precisely with AI.
The current scenario of AI in healthcare backed up by ML is smarter enough to identify tumors. Besides, artificial intelligence in healthcare also helps in diagnosing severe diseases efficiently.
In this article, we compiled a list of the best applications of AI in the healthcare sector.
The best applications of AI in the healthcare sector
Applications of AI in healthcare are incredible. The AI technology for the healthcare sector is driving abundant benefits for care service providers. Especially with the use of predictive analytics, AI is transforming the healthcare industry rapidly.
Here are the best benefits of AI in healthcare
- AI for fast diagnosis
AI machines can process vast historic patient data faster for ensuring quick and accurate treatment decisions. AI can predict disease faster than a physician. Thus, artificial intelligence in healthcare supports practitioners for quicker data access for providing the right treatment at the right time.
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- AI for drug development
Artificial intelligence is widely deploying by pharmaceutical firms for developing new drugs to tackle novel diseases. Companies are using AI for drug research and development functions.
- AI for boosting admin tasks
This application is widely used for automating health insurance services. The insurance companies in the healthcare industry are relying on AI for boosting their internal processes. Artificial intelligent systems help them in processing claims automatically with human interference.
AI-powered automation systems analyze hundreds of claims and accurately checks for the credit eligibility of each client.
- AI robots for surgery
The robotic surgery includes minimum cuts and slits. Besides, compared to physicians, robots perform surgery with less pain and little incision line. Accordingly, telemedicine is also gaining popularity nowadays. Remote surgery using robots and telemedicine with assistants are giving tremendous benefits to care service providers.
Thus, the future of surgery using AI in healthcare is stress-free. Thanks to such advanced AI technology for the healthcare industry.
- AI for post-discharge services
Few advanced AI apps for healthcare allows doctors to help patients post-discharge. Patients can get detailed data of medication, follow-ups, and physician contact details.
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- AI personal nursing assistants
It is one of the best applications of AI in healthcare or AI in medicine. As of research, over 50% of patients are comfortable and safe being with virtual nursing assistants. The AI and ML-powered virtual nursing assistants operate with voice and checks patients on time.
- AI for quick navigation
Nobody knows when a person needs emergency treatment. User-friendly AI-powered mobile apps act as a bridge between hospitals and clients. The best example of AI in healthcare for this application is USM’s AI healthcare app.
This next-gen. AI app for healthcare benefits patients to find the nearest healthcare centers. Accordingly, it also gives data on room availability, fab facilities, and so on. If you are a healthcare service provider, get this AI app for healthcare for providing quick and personalized services to clients.
Other Benefits of artificial intelligence in healthcare
#1 Aware Of Regularity Frameworks
In the recent past, healthcare regulations in the United States are updating to keep up with the evolving digital healthcare market. The U.S. Food and Drug Administration (FDA) has been taking incremental phases to amendment the existing rules and regulations. Recently, it was introduced the “Digital Health Innovation Action Plan” to guide the agency’s role in advancing effective digital health technologies.
Besides, the FDA also focused on a digital health software Pre-Cert Pilot Program. It is enrolling software-as-a-medical-device (SaMD) developers in this project. This pilot project helps the FDA to determine the performance indicators that are needed for per-certifying the product. Using this, the FDA helps developers in identifying new ways of product approval procedures that are seamless.
Accordingly, another regularity framework, “Policy for Device Software Functions and Mobile Medical Applications” was introduced in 2019 for higher-risk software. This new policy comprises various guidance documents that label how the agency plans to regulate software that helps in clinical decision support (CDS). The CDS software identifies a patient’s medical conditions as it uses ML algorithms.
#2 Achieving FDA Approval
To comply with the changing FDA approval processes, software developers must consider how to design and roll out their products under the FDA rules. Particularly, developers should focus on achieving FDA approval for the software which comes under the higher risk category.
Here, artificial intelligence-powered diagnostic tools and applications come in place. The developers should be more focus on FDA rules when they develop AI-powered healthcare tools and software. As AI is evolving across all sectors, the healthcare industry is also investing in AI to automate its medical diagnostic processes.
Software Update is a major concern that developers face today. Because, based on the market requirements, the developers will update the existing software products. They will add new features to advance the functionalities using emerging AI and ML technologies. But, when they change the technical description of the software, the FDA approval status for the old version of the software will be at risk.
Similarly, organizations must know the company’s product development plans and approach that they follow to get FDA approvals. This provides investors a clear variation of the company over its competitors in the same industry.
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#3 Black-Box Nature of AI Is Hampering Its Growth In Clinical Applications
Yes, artificial intelligence is a black-box in its nature. This is one of the major drawbacks of the rapid adoption of AI-based applications in healthcare.
We’ll brief it out. Can all healthcare AI-powered applications track and assess the decision making procedure when a negative outcome happens? Will the set of trained data to the ML algorithms is visible to users? Will the reason for a negative outcome is identified by the technology itself?
The developers should focus on all the above points while designing an AI-powered software for healthcare. Because, if your software is posing more negative outcomes, then the application will be banned in the market and the efforts you put on design, development, and getting approvals will be wasted in minutes.
Accordingly, AI-systems need more data to perform the tasks that they assigned to do. But, if you feed the AI systems with wrong data, it will provide incorrect conclusions such as misdiagnosis and improper treatment recommendations. Error Detection algorithms help you out in this scenario. Thanks to technology developments.
Currently, many healthcare service providers are using artificial intelligent-based medical diagnostic devices to provide better services and optimize patient diagnosis process. For instance, FDA approved AI-powered imaging diagnostic software/tools are helping clinicians in diagnosing and treating various health conditions such as cardiovascular disorders, diabetic conditions, and cancer.
However, the adoption of these AI tools is sluggish in the market. There is a need to publish the AI’s benefits in healthcare. More awareness of artificial intelligence in healthcare to witness industry adoption and get the credibility of AI technology.
The Future of AI in Healthcare
Implementation of AI in healthcare was at the pre-mature stage. Without significant investments, AI adoption in healthcare is slow and difficult. The market researchers are estimating that the clinical health AI applications will save $150 billion per annum for the United States economy by 2025.
Artificial intelligence in healthcare is used for multipurpose. AI can sense machines, learn, and perform both clinical and administrative tasks. Hence, health AI will augment every task done by humans intelligently and automatically. The graph below depicts the most promising healthcare applications of AI that are attracting more investments.
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On the global artificial intelligence healthcare market front, the investments are stunning and are increasing every year. Both the public and private sectors are heavily investing in health AI.
Every healthcare company is in plans of implementing AI strategies to become competitive in the market. From clinical diagnosis and treatment to robotic surgery and drug development, AI plays an essential role in healthcare. The healthcare AI
in healthcare is slow, health AI will completely change the structure of the existing healthcare market in the next decade.
Yes, the complete roll out of AI will take years, but AI technology, ML and predictive analytics together bring an advanced healthcare solution that was never before available.
According to researchers, AI is widely used for automating admin and operational tasks in the near term future.