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Lets work together to identify challenges in healthcare and discuss whether they can be addressed by the application of machine learning and AI


Who are we?

AI for the Rest of Us is a platform that facilitates discussion, problem identification and problem solving to create a positive impact on public health by leveraging machine learning and artificial intelligence. Our meet ups aim to connect participants with thought leaders in Digital Health and AI and to encourage people to learn and mentor each other.

What do we do?

Our team creates opportunities for people to get-together to surface challenges in healthcare and to brain storm ways of addressing those issues potentially using machine learning and AI. Each of the sessions will start with an informal discussion with the group led by recent events in the healthcare industry. This will be followed by a conversation with a guest speaker followed by Q & A.

Why do we do it?

We care about patient-centric, data-driven, evidence-based, accessible, and affordable healthcare solutions. We believe in the power of machine learning and AI - but we also question it. We want to engage the community in a dialogue that enables learning and identification of problems that are plaguing the healthcare system. We get excited about connecting the right people at the right time. We understand the value of mentorship.

Who should participate?

Researchers, Engineers, UI/UX designers, Economists, Policy makers, Design Strategists, Healthcare evangelists, Medical School Students, Professors, Entrepreneurs, Students interested in learning about the capabilities of AI, and ANYONE who is interested in engaging and creating an environment to discuss how AI can be leveraged to solve problems in public and population health.

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Digital Health

Cyber health security, Digital Pharmacy solutions, Connecting patients with doctors, Telemedicine, Smarter algorithms, Social acceptance and ease of AI adoption, Medical School education and adoption technologies

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Therapeutic Areas

Neurology, Oncology, Ophthamology, Diabetes Type 1 and 2, Fetal health etc

Assessing impairment from speech disorder, Automated assessment of MRI scans, POC detection of disease progression,  Efficient extraction of Treatments information in Clinical Literature and Trial Eligibility, Monitoring Fetal and Geriatric Health

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EHR incorporation and integration, ICU functioning, Treatment planning, Automating workflow managemnt, development of inter-operatbility, Prediction of ICU Mortality, Reduction of Re-Admission, Predicting costs, Reducing unwarranted in hospital care

... more