Incorporating Artificial Intelligence In Indian Healthcare Sector

Every year, around 50,000 individuals graduate to become certified doctors. In order to maintain the minimum doctor-patient ratio, as suggested by WHO, India will need 2.3 Mn doctors by 2030. If there was ever a requirement to push healthcare in India into the future, it is now! Today is the time when we can see significant disruption in the Indian healthcare industry. Much of this is credited to the level of involvement of artificial intelligence, big data, cloud, machine learning and deep learning, and wearables or fitness trackers which are connecting the organizations with the individuals.

To start with, Artificial Intelligence or AI as we call it has the potential to transform the diagnosis and cure of multiple diseases which were considered incurable a decade ago. Artificial intelligence in Indian healthcare industry rely on a paradigm shift in the way the machines read electronic data of patients, including their age, medical history, tests, medical images, DNA sequences, and other factors to fuel treatment.

Dr. Eric Topol in his book, Deep Medicine, has sited organisations and their role in developing tools to analyse health conditions. One such tool that Google has developed can precisely detect diabetes relatively accurate. The software has a sensitivity score of 87-90% and an accuracy of 98% while detecting diabetic retinopathy.

A team of advanced doctors in London have come up with a treatment approach for more than 50 eye diseases having 94% accuracy. To understand the level of precision, their results were compared to that of international eye specialists. As per the reports of this experiment, the doctors missed a dew reference points but the machine didn’t, any.

In China, on the other hand, Artificial Intelligence is being used to diagnose the presence polyps on the colon during a colonoscopy. When the diagnosis of a gastroenterologist was compared to that of a machine, the latter had 9% more chances of early detection. The beauty of this experiment was that the machine didn’t miss the tiny polyps, even the ones with a size less than 5mm which were otherwise easier for the doctors to miss.

Our mobile phones are not only performing functions they were designed for but also collecting our digital footprints and analysing our behavior on screen. Not just the obvious audio snooping, even our eye-tracking data collected while we freely watch TV can determine neurodegenerative eye diseases, as cited in an article by Artificial Intelligence in Medicine (2018) Journal.

In India, young startups are coming together to help doctors diagnose chronic diseases at an early stage. With the help of predictive analytics and machine learning, these startups are creating diagnostic tools that could help specialists diagnose faster and more accurately. A medical wearable startup, ten3T, has developed medical-grade wearable devices attached with a Cicer (device embedded with multiple sensors) to help monitor patient’s health, even at home. mFine, Bengaluru based healthcare startup has close to 1200 diseases in the system to give 85% of accurate diagnosis.

AI does the hard work of compiling the complex identification trigger points and creating a pattern out of this data on an intensity level and speed beyond any human being’s capability. AI has the capacity to take charge of rural areas with a mobile device, without having the doctors to travel from village to village. Evidently, artificial intelligence and deep learning are the hope of new-age technology, which if correctly harnessed, can help doctors and scientists make better decisions in growing Indian healthcare industry further.

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