Use Cases of AI in Healthcare
With IBM Watson, virtual health assistants, medical imaging diagnostics, the AI-powered medical care center in China, etc., Artificial Intelligence (AI) has already made its mark in the healthcare sector. All major players in the healthcare sector today look to leverage AI one way or another to improve healthcare using AI. Let’s look at some real-life use cases of artificial intelligence in the healthcare sector.
AI in Medicine and Disease Predictions
As proved by IBM Watson’s performance in multiple cases, AI-based systems are much faster in diagnosing a medical issue and predicting the underlying disease. Further, the field of medicine is research-intensive and requires researchers to undertake extensive studies and experimentation. AI-based systems can perform research on behalf of the researcher and present viable options to solve the problem at hand.
Research and Advanced Analytics for Patients
A rising number of doctors today depend on machines in roles varying from regular check-ups to major operations, to improve the health of their patients. AI can not only contribute towards smarter and more adaptive machines but also can detect faults in these machines well in time. Knowing the defects or faults in time will minimize the repair cost and cost of the damages that may have been caused if a fault wasn’t detected. Further, AI-powered machines can suggest surgery or treatment paths best suited to the patient’s condition.
Health care Bots
Thanks to the Artificial Intelligence NLP services as Chat bots are rapidly taking over the customer service process. On the same lines, healthcare bots can help patients resolve their issues faster as compared to traditional healthcare counseling or sessions with human healthcare personnel. These bots can not only help in scheduling follow-up meetings, maintain a digital record for the user, and help set reminders at the user end, but also, these bots can make the process of bill payment hassle-free and smooth (by facilitating online bill payment through the bot).
Medical Imaging and Smart Diagnostics
Aided by AI-based computer vision capabilities, smart medical imaging, and diagnostic systems today provide a much clearer and informative picture of human anatomy. Such images help in detecting anomalies and features of human anatomy that may have gone unnoticed through the traditional systems.
Doctors usually have to refer to an enormous amount of medical literature when dealing with sensitive or critical medical situations. This process is both tiring and time-consuming. Further, the smallest of mistakes while going through the medical journals may prove fatal to the patient at hand.
AI-based natural language processing (NLP) systems shorten this process significantly by filtering relevant information for the doctors and narrate it to the doctors if required to help them further speed up the process.
AI systems, when used to maintain patient records, enable doctors to look at the patient’s medical history and previous prescriptions, along with viable and more efficient drugs suited to the patient profile.
Each medicine available today has been developed after years of experimentation and extensive clinical trials. This process is costly and time-consuming. AI-based systems can speed-up this process and hence reduce the costs involved in developing drugs. For example, Atomize used the fastest Canadian supercomputer with its AI-based program to find alternative medicines for Ebola. This program found potential cures for Ebola within a day.
Using AI systems that have computer vision and smart medical imaging capabilities backed by deep learning models, researchers have improved the accuracy of cancer detection in various parts of the human body. These AI-based systems also reduce the time (by almost half) and effort required in diagnosing cancer.
While AI has a long way to go before becoming entirely autonomous for its application in the healthcare system, even at the current efficiency level, AI is helping the healthcare sector enormously. The healthcare sector has a high potential to use AI systems further to improve the services provided to its clients and patients.
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