By S Ramadorai and Arvind Singh
Over the past decade, artificial intelligence (AI) has multiplied productivity across a range of human endeavours. It has been reiterated over the years that AI has the potential to usher in a new era of patient-care by guarding against human error and inadequacies, enhancing speed and accuracy of healthcare services, and making expensive procedures accessible.
Some view the pace at which AI is transforming healthcare to be not up to projections. However, it is important to note that not only have we made significant headway in AI adoption in healthcare, but we are also witnessing an increasing use of AI in a range of complex healthcare functions and processes—from reading scans to predicting risks.
We have to delve a little deeper to understand what AI is and why it holds tremendous promise. AI does two things primarily. It mimics human intelligence that exhibits traits associated with a human mind such as learning, problem-solving, and decision-making to carry out tasks at unprecedented speed and efficiency. On the other hand, it enables cumulation of experiences at a level that is humanly impossible. One of the unique strengths of human decision-making is the experience that enables us to rationalise thoughts and actions based on situations encountered in the past. AI breaks the barrier between individual experiences and enables the development of what we call ‘cumulative wisdom’. AI, along with machine learning (ML), allows the integration of innumerable experiences through huge amounts of unstructured data programmed into a machine that is then used by the machine to automatically learn from and adapt to new environments without being assisted by humans. Thus, AI helps us to grow intelligence that far exceeds the capabilities of an individual human mind.
Also read: Towards distributed consensus
For instance, an AI-based system designed to interpret MRI or X-ray scans would have huge amounts of imaging data fed into the system, collected from thousands of scans over time. The AI algorithm learns from every decision it makes and thereby continues to improve its ability to accurately interpret an image. AI software reading medical imaging can in general match, or in some cases, outperform human radiologists.
AI’s role in healthcare has gained ground after the onset of Covid-19, as hospitals started using AI to detect extent of lung damage as SARS-CoV-2 led to rapid deterioration of pulmonary health. While AI use still remains widespread in radiology, it is increasingly being used for purposes such as preventive health checks.
A number of start-ups have emerged over the past few years where they are exploring various applications of AI to transform healthcare. We look at a few such innovations that are creating significant impact in patients’ lives and changing the course of healthcare in the country.
The first is Bengaluru-based Niramai that has developed a novel software-based medical device to detect breast cancer at a much earlier stage than traditional methods or self-examination. Their solution is a low-cost, automated, portable cancer screening tool that can be operated in any clinic. The imaging method is radiation-free, non-touch, not painful and works for women of all ages. The core technology of the solution is cloud-hosted and uses Big Data analytics and patented ML algorithms. This enables a large number of scans to be conducted and processed, with a high degree of accuracy for early detection of breast cancer. The fact that the device is a handheld one enables screening to take place in any community setting, and can be used for preventive health check-ups in rural and semi-urban areas.
BrainSightAI is another start-up that uses AI to interpret functional MRI (fMRI) scans that allow for imaging of areas of the brain that are functionally active. Brain activity increases blood flow to the relevant part resulting in an increased oxygen uptake. The AI-based interpretation of these images can predict any collateral damage that may occur if brain tumours or other lesions were to be excised. This enables evidence-based treatment where surgeons can conduct surgeries in a more informed way.
There are more start-ups that are pioneering healthcare innovations with AI component in other areas, namely, Tricog that has a product to interpret and analyse ECG reports within minutes, and SigTuple that builds intelligent screening solutions to aid diagnosis in pathology and ophthalmology. A similar development that deserves a mention is a collaborative initiative between Indian Institute of Technology-Guwahati and Sankaradeva Nethralaya-Guwahati. The research team has developed a point-of-care testing device that can detect diabetic retinopathy at an early stage, without the need for invasive testing. As the retina is an extension of the brain, and retinal vasculature is almost identical to blood vessels in the brain, it should be possible, with the help of AI, to diagnose conditions such as dementia and Alzheimer’s, and blinding retinal disorders like glaucoma. As more data is gathered, it should be possible not just to diagnose but also to monitor the progress of these disorders. The team has also filed an Indian patent for this idea and device.
We are currently witnessing progress in clinical usage of AI in healthcare. However, AI’s role can extend much beyond, where it can play a defining role in other areas—be it delivery of services through tele-health, patient engagement and administration of healthcare systems, precision medicine for individualised treatment, or research and development of new medical interventions. Countries with limited availability of resources and assets can bridge the demand and access gap of healthcare services and products through the use of AI and other related technologies.
The Centre too is focusing on AI to help it track disease outbreaks across the country. The National Centre for Disease Control (NCDC) is developing a platform that will scan all media reports related to health, to create a database of outbreaks of 33 diseases—some with the potential to become epidemics.
While no technology can claim to be a silver bullet that can address all challenges of a system as complex and wide-ranging as healthcare, AI still qualifies as something that can lead to radical transformations. When deployed thoughtfully and ethically, AI has the potential to upend long-accepted constraints about how the healthcare system works. It can redefine the relationship between cost, accessibility, quality and outcomes for the better. All we need is for people to unleash their entrepreneurial capabilities to make the most of the AI-led opportunities in healthcare innovation.
Writers are respectively, former vice-chairman, TCS, and eye surgeon and consultant, devices and processes