Guest Column/Anil Bhansali, vice president of engineering and head of India Development Centre at Google Cloud
The Indian health care market is on a high-growth path, with significant focus on digital transformation. As per NASSCOM, data and AI in health care have the potential to add about $25 billion to India’s GDP by 2025. Large corporations and hospitals are investing heavily in digital health to make health care more accessible to Indians.
Triggered by the pandemic, the health care industry witnessed public health officials, vaccine developers, equipment manufacturers and essential workers take life-saving actions and respond to the exceptional challenges of our time. The government of India has undertaken initiatives such as the Unified Health Interface to create a network of open protocols that enable the interoperability in health services, accelerating the digital health adoption in India.
With the increase in adoption of digital health in India, AI and machine learning will have a critical role to help advance health care and make it more accessible to billions of people. As an example, Google Cloud works closely with the largest health care system in India to integrate AI models to build products like a symptom checker that can help patients understand their primary symptoms. In another case, we work with very large health systems to help them expand their presence through our telemedicine solution and enable medicine ordering for chronic patients in a simple and easy-to-use platform. Automated Retinal Disease Assessment (ARDA) is a joint collaboration by Verily and Google to prevent blindness by expanding access to quality eye screening. The initial focus of ARDA is on using machine learning technology to detect diabetic retinopathy and diabetic macular oedema.
Recent progress in large language models (LLMs)―AI tools that demonstrate capabilities in language understanding and generation―has opened up new ways to use AI to solve real-world problems. However, unlike some other LLM use cases, applications of AI in the medical field require the utmost focus on safety, equity and bias to protect patient wellbeing. To work towards developing AI tools that can retrieve medical knowledge, accurately answer medical questions, and provide reasoning, we have invested in medical LLM research. Last year, we built Med-PaLM, a version of PaLM tuned for the medical domain. Med-PaLM was the first to obtain a “passing score” on US medical licensing-style questions. Recently, our next iteration, Med-PaLM 2, consistently performed at an “expert” doctor level on medical exam questions, scoring 85 per cent.
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There is enormous potential for AI to augment diagnostic and treatment planning processes, especially through partnership, to help bring high-quality care to communities that need it most. Private and public sectors are learning from, and increasingly partnering with, the social sciences, public health, biomedical informatics, computer science, public policy and community groups around how to build more equitable and inclusive consumer products and health IT strategies. AI can help accelerate Google’s mission of billions of healthier people by making sense of complex information, aiding medical and scientific discoveries, democratising access to health, scaling expertise, addressing the world’s most critical health challenges and reducing medical errors.