AI + Innovative Healthcare
Supporting better global healthcare access, research and systems through AI.
AI for Good Foundation believes in the positive potential of AI for better equity, access, and the development of real-time public health solutions. Our work spans policy and implementation and we welcome interested partners in supporting AI as an innovative health solution.
Our AI & Innovative Health program falls within the Intelligent Cities Project. Our team works with municipalities globally to assess and implement the sustainable use of AI. In addition to our Intelligent City Assessments, we speak internationally and convene seminars on timely issues affecting AI and innovative healthcare. Topics include: accessibility, bias, private-public partnerships, and feasible roll-out of AI applications.
We advocate for a culture of doctors being evaluated on the health of their population, rather than on outcomes after adverse health events. One of the cornerstones of equity in such a system is access, and access is especially a concern for the elderly, homeless, and children. We believe in equitable healthcare delivery within municipalities and resource-strapped regions. As the world constantly adapts to global health emergencies, especially the COVID-19 pandemic, we support the ethical and strategic use of AI to accelerate progress.
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Introducing the AI & Innovative Health Advisory Committee
James Hodson
CEO, AI for Good Foundation
United States
Christian Kauth
Researcher and software developer
Switzerland
Asra Haq
Healthcare technology professional
Canada
Senthujan Senka
ML medical researcher and state health professional
Canada
Priyanka Challa
Analyst, virtual healthcare for state health system
Canada
Ricky Purnomo
Data analyst, Ministry of Health
Singapore
Tenzin Migmar
ML Research and Sustainable AI Policy Intern at AI for Good
Canada
Katie Johnson
VP of Implementation at Happify Health
United States
Hebbah Elgindy-Johnsson
Senior behavioral scientist
Sweden
"Healthcare practices are undergoing massive transformational changes globally in response to major events, the current paradigm has been challenged with the recognition of AI augmenting clinical practice. We are entering a new era in which new systems of financing healthcare are emerging, as we move towards a value-based system centered around the patient experience and outcome. AI has the potential to help nations achieve this goal and thus bring us closer to creating equitable, sustainable, and most importantly universal healthcare systems."- Senthujan Senka
Resources
Shared Datasets
Created by the World Health Organization, this dataset captures the number of births attended to by skilled health personnel relative to the total number of live births in the same period.
Maternal Mortality refers to the number of pregnancy related deaths per the total number of hospital deliveries per 100,000 live births. The UN has set target 3.1 to reducing maternal mortality; this entry on Our World in Data tracks global data on maternal morality to record progress towards target 3.1.
A repository of global, regional, and country data on immunization that tracks trends in areas such as vaccination coverage and reported cases of vaccine-preventable diseases.
This dataset falls under indicator 3.3.2 for the Global SDG indicator Database which is referenced for the Secretary-General’s annual report on Progress towards the Sustainable Development Goals.
This dashboard visualizes the global COVID-19 situation by region, country, territory, and area.
Global data on the % of the total population pushed into poverty as a result of health care expenditures. This dataset demonstrates the correlation between SDG target 1.1: the eradication of global poverty and SDG 3.8 universal healthcare coverage.
Research
DIAGNOS and the CHUM are launching the testing phase of autonomous artificial intelligence solutions dedicated to diabetic retinopathy screening BROSSARD, Quebec, May 26, 2022 (GLOBE NEWSWIRE) — Diagnos Inc. (“DIAGNOS”, the “Corporation” or ”we”) (TSX Venture: ADK) (OTCQB: DGNOF) a leader in early detection of critical health issues through the …
AI cracks 50-year-old ‘protein folding problem’, say researchers A problem dating back five decades may have been cracked by artificial intelligence created in the UK, paving the way for faster development of treatments and drug discoveries for protein. The so-called “protein folding problem” has long been one of biology’s …
Computer science researcher plans to use machine learning to improve Cancer Prognosis Research begins this July on a project to apply big data to cancer treatment protocols Cancer Prognosis. Computer Science and Engineering Assistant Professor Tin Nguyen has received a $490,039 National Science Foundation CAREER award to develop new machine …
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