We have earlier explored how AI is boosting healthcare systems worldwide, especially in this age of the pandemic. The applications of AI in medicine know no bounds. Reports suggest when AI is coupled with other manner of health data, it can provide some valuable insights which can help healthcare providers treating sleep disorders, and it will also help in delving deeper into the human understanding of the role of sleep in maintaining good health. Not only this, it is widely accepted that AI can also streamline everyday working of the medical care system and put patient care at the forefront of the priorities of the sleep disorders team
What is required in the current state of affairs is to develop best practices which will help in incorporating the new and evolving technology into the day-to-day operations of the healthcare providers and other stakeholders at the same time maintaining transparency and quality standards. When mobilized in a systematic way with human inputs, AI has the potential to improve the working of sleep medicine and use sleep science towards the upkeep of health and well-being of the patients.
It is no secret that the review of sleep disorders and the course of their treatment lies in the use of polysomnography or sleep study which is a test to diagnose sleep disorders. Polysomnography brings home a huge amount of labeled electrophysiological data. Sleep science can thus benefits by the use of big data by the way of creation of AI-based programs which can help in the following goals: a) A precise classification and diagnosis of disorders as well as diseases b) disease prediction and prognosis, c) division of the disease into subtypes, d) accurate and automated instrumentation via sleep scoring, and e) customization of treatment and much more.
By their very nature, ML algorithms and programs pick up patterns by adjusting variables and improve performance of prediction, classification, clustering etc. All this helps in a greater understanding of the Therefore, they provide powerful tools for understanding links within datasets available.
Electrophysiological data, which is derived from PSG recordings in huge amounts, acts as the base for AI applications. When this data is combined with factors such as genetic information, demographics, as well as behavioral and lifestyle data, AI becomes a powerful tool in providing hitherto unknown insights for an informed diagnosis and clinical care for patients with sleep disorders.
Another area in which sleep sciences stand to benefit from AI is the health of the population. AI can help with deeper insights and understanding about the intrinsic role of sleep on human health on a very big scale
It’s most obvious in the digital media space, from click buys to personalized web experiences. For marketing, the AI journey has just kick-started, while in the tech sector it has been applied for a while now. We are still at an early stage where inroads are being made into AI content via chatbots and even some explanatory content creation but what will make anyone jump up and embrace it is when we will start seeing a lot of mainstream content being created by AI.
Prior to joining Infinite Analytics, Richard served as the CFO of CrowdFlower, COO and CFO of Phoenix Technologies, as a member of the board of directors and chairman of the Audit Committee at Intellisync, and previously as CFO and executive vice president strategy and corporate development at Charles Schwab.
Pravin Gandhi has over 50 years of entrepreneurial operational and investing experience in the IT industry in India. He was a founding partner of the first early stage fund India - INFINITY. Subsequently a founding partner in Seedfund I & II. With over 18 years of investing experience, he is extensively well networked in investment and entrepreneurial scene and is an active early stage angel investor in tech & impact space. Pravin holds a BS in Industrial Engineering from Cornell University, and serves on the board of several private corporations in India. He is on the board of SINE, IIT Mumbai Incubator.
Puru has his Masters in Engineering and Management from MIT. Prior to MIT, he worked with Fidelity Investments building electronic trading products and high volume market data processing applications. He has completed his BE from VJTI, Mumbai.
Deb Roy is Professor of Media Arts and Sciences at MIT where he directs the MIT Center for Constructive Communication, and a Visiting Professor at Harvard Law School. He leads research in applied machine learning and human-machine interaction with applications in designing systems for learning and constructive dialogue, and for mapping and analyzing large scale media ecosystems. Deb is also co-founder and Chair of Cortico, a nonprofit social technology company that develops and operates the Local Voices Network to surface underheard voices and bridge divides.
Roy served as Executive Director of the MIT Media Lab from 2019-2021. He was co-founder and CEO of Bluefin Labs, a media analytics company that analyzed the interactions between television and social media at scale. Bluefin was acquired by Twitter in 2013, Twitter’s largest acquisition of the time. From 2013-2017 Roy served as Twitter’s Chief Media Scientist.
Erik Brynjolfsson is the Jerry Yang and Akiko Yamazaki Professor and Senior Fellow at the Stanford Institute for Human-Centered AI (HAI), and Director of the Stanford Digital Economy Lab. He also is the Ralph Landau Senior Fellow at the Stanford Institute for Economic Policy Research (SIEPR), Professor by Courtesy at the Stanford Graduate School of Business and Stanford Department of Economics, and a Research Associate at the National Bureau of Economic Research (NBER).
Akash co-founded IA while studying for his MBA from MIT. Prior to MIT Sloan, he co-founded Zoonga. Before this, Akash was an engineer with Oracle in Silicon Valley. He has completed his M.S from University of Cincinnati and B.E from the College of Engineering, Pune.