“Artificial Intelligence for sure over the long run is the most powerful technology the humans will invent,” Google CEO Sundar Pichai at Google I/Q 2018. Google is speculating that the future of healthcare is going to be structured data and AI. It seems to be going after the healthcare space from every possible angle.
Artificial intelligence simplifies the lives of patients, doctors and hospitals by performing chores that are typically done by humans, but in lesser time, at a fraction of the cost with almost zero casualty and precision. AI is reinventing — and reinvigorating — modern healthcare through machines that can predict, understand and act upon it. Incapability to diagnose a possible ailment can be a serious threat. AI can not only predict but also diagnose diseases at a faster rate than most medical professionals/ pathologies.
AI can help predict cardiovascular risk, and detect it non-invasively. Diabetic retinopathy which is the leading cause of eye cancer in India, Google is working with eye hospitals like Shankara to deploy Machine Learning for an enhanced screening of the eye and detect chances of cancer. The company would also conduct on-field trials that would help in the diagnoses of diabetic retinopathy in developing countries.
While diabetes management is relatively well perceived , there’s a gap in diabetes detection. Your pancreas is connected to your autonomic nervous system (ANS), small changes in heart rhythm could potentially help detect development of the disease. A startup, Cardiogram, uses heart rate to monitor and predict disease, detected diabetes with 85% accuracy using AI and heart rate. A passive heart monitor that uses optical sensors and machine vision. It has a disease detection component, detecting blood flow issues in areas like the brain for stroke detection or detecting cardiac abnormalities like an arrhythmia, which could indicate cardiovascular issues.
Other areas where the AI will be functional are in the poorly understood ‘Parkinson’s disease’, a disease without a known cause or cure ‘Multiple sclerosis’, cancer detection, mental and behavioural health, and other chronic and pulmonary diseases. One of the biggest obstacles in healthcare is that data accessibility is strictly for organisations and there’s very little inter-operability between systems. It has to be noted that it is difficult to integrate data across differing EMRs even within the same compound. Creating new data infrastructure with cloud accessibility, tools for doctors and nurses to augment their expertise, can particularly benefit areas where there is little or no access to skilled surgeons or doctors in general, such as rural areas.
Robotic precision surgeries, instrumentation, advanced visualisation, data analytics, AI can improve the health of large segments of the population at once.