Pioneering precision Medicine for women
Female Medicine through Machine Learning
MIT’s Female Medicine through Machine Learning (FMML) leverages AI and real-world data to pioneer precision medicine for women, addressing overlooked gaps in female health and transforming disease discovery, detection, and delivery.
About UsOur Vision
MIT’s Female Medicine through Machine Learning (FMML) will pioneer precision medicine for women. It aims to close the women’s healthcare gap by pioneering the development of precision medicine for women using artificial intelligence and real-world health data sets.
FMML research body
Our Approach
Female data (cells, animals, humans) accounts for only ~5% of the cumulative research body. Women have sex-specific cells, organs and conditions that modulate all other physiological functioning. In addition to yielding female-only diseases, they create differential disease prevalence, diagnostic symptoms, drug responses, and treatment needs for all disease. Incredibly, this remains largely unaddressed in current medicine.
Our precision medicine approach will leverage two breakthroughs: artificial intelligence (AI) and real-world datasets (RWD) in medicine. AI allows rapid data analysis at scale while real-world datasets (RWD), unlike medical research ones, are 50% female.
We will focus on three areas:
Our precision medicine approach will leverage two breakthroughs: artificial intelligence (AI) and real-world datasets (RWD) in medicine. AI allows rapid data analysis at scale while real-world datasets (RWD), unlike medical research ones, are 50% female.
We will focus on three areas:
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We are just launching. If this intrigues you and want to learn more, reach out.
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Female Medicine through Machine Learning
Laboratory for Information and Decision Systems
Massachusetts Institute of Technology
Room 32-D608
77 Massachusetts Avenue
Cambridge, MA 02139
Massachusetts Institute of Technology
Room 32-D608
77 Massachusetts Avenue
Cambridge, MA 02139
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