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It's the data, stupid: Inflection point for Artificial Intelligence in Indian healthcare.
Ramaswamy, Anjali; R Gowda, Naveen; Vikas, H; Prabhu, Meghana; Sharma, D K; Gowda, Praveen R; Mohan, Deepak; Kumar, Atul.
Affiliation
  • Ramaswamy A; Department of Obstetrics & Gynecology, All India Institute of Medical Sciences (AIIMS), New Delhi, India.
  • R Gowda N; Department of Hospital Administration, All India Institute of Medical Sciences (AIIMS), New Delhi, India.
  • Vikas H; Department of Hospital Administration, All India Institute of Medical Sciences (AIIMS), New Delhi, India. Electronic address: vickygaddi@aiims.edu.
  • Prabhu M; Department of Nuclear Medicine, Institute of Liver and Biliary Sciences (ILBS), New Delhi, India.
  • Sharma DK; Medical Superintendent, All India Institute of Medical Sciences (AIIMS), New Delhi, India.
  • Gowda PR; Toyota Kirloskar Motors Private Limited, Bangalore, Karnataka, India.
  • Mohan D; Malomatia India Technologies Private Limited, Pune, Maharashtra, India.
  • Kumar A; Employees' State Insurance Corporation, Head Quarter, New Delhi, India.
Artif Intell Med ; 128: 102300, 2022 06.
Article in En | MEDLINE | ID: mdl-35534144
ABSTRACT
Indian healthcare is fast growing and with significant chunk of it being in small, fragmented, informal sector; Artificial Intelligence (AI) is pegged as a magical tool for a better healthcare system. There is an inclination to merely mimic the US approach in the on-going policy making and legislative exercises, which can have serious fallouts for Indian healthcare. India needs a different approach to suite her unique requirements. In this regard, each of the five stages in AI development lifecycle has been analyzed in the light of current on-ground realities. These boil down to three fold challenges of how to increase adoption of digital health, prevent data silos and create maximum value from data. Availability of quality data for value addition without barriers and restrictions is the common denominator for leveraging the full potential of AI. This requires liberal policies enabling secondary use of data in developing countries with rapidly growing healthcare sector akin to India. This has to be carefully balanced with data privacy and security. Restrictive healthcare data policies and laws can slow down adoption of digitization, perpetuate status-quo, be biased towards the incumbent players, cause Industry stagnation and thus will do more harm than good. It is therefore the data policies that will make or break AI in Indian healthcare.
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Full text: 1 Database: MEDLINE Main subject: Artificial Intelligence / Delivery of Health Care Country/Region as subject: Asia Language: En Journal: Artif Intell Med Journal subject: INFORMATICA MEDICA Year: 2022 Type: Article Affiliation country: India

Full text: 1 Database: MEDLINE Main subject: Artificial Intelligence / Delivery of Health Care Country/Region as subject: Asia Language: En Journal: Artif Intell Med Journal subject: INFORMATICA MEDICA Year: 2022 Type: Article Affiliation country: India