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MARCH OF PRECISION MEDICINE

India Today

|

January 15, 2024

THROUGH ITS ABILITY TO MAKE SENSE OF HEAPS OF DATA, AI CAN TRANSFORM INDIA'S HEALTHCARE LANDSCAPE BY REDUCING COSTS, IMPROVING EFFICIENCY AND FACILITATING PERSONALISED INTERVENTIONS

MARCH OF PRECISION MEDICINE

The medical community has rapidly acknowledged the potential advantages of Artificial Intelligence (AI) since its emergence in the 1950s. In 1959, it was determined that machines could interpret symptoms diagnostically. By 1960, physicians projected that computers could significantly augment their cognitive abilities by the year 2000. Availability of data through connected devices, increased storage capacities, enhanced computing are a few enablers of AI adoption across industries, including healthcare. From everyday health apps to high-precision analysis of complex medical scans for early diagnosis, to helping tailor treatment plans, AI is useful in drawing insights from a large amount of clinical data for better disease management, prediction and designing outbreak strategies. Machine learning, which involves fitting models to data and learning through training, is utilised extensively in healthcare, especially in precision medicine.

AI is augmenting our ability to think and take considered action as people and clinicians. This holds the promise of significantly contributing towards transforming India’s healthcare landscape, which remains riddled with historical challenges, even though healthcare has been one of the biggest success stories of our time. The unstoppable forces of changing demographics, such as an ageing population, altered lifestyle and disease patterns, and climate change, are posing challenges that can’t be met through just public-private spending, structural changes in the healthcare network or increasing the number of medical practitioners and allied professionals. Expert use of AI offers us an unparalleled opportunity to surmount challenges both old and new despite increased noise and fear about the machine replacing man across functions.

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