Human Health Is Not One Size Fits All

Princeton Precision Health is a cross-cutting initiative that uses data science to transform human health at all levels: from molecular to social to environmental, with the goal of enacting smart policy and evidence-based clinical practice. We are an interdisciplinary team of researchers from a wide variety of fields, including computer science, psychology, public policy, and clinical practice, collaborating to solve complex problems and reduce bias in human health, policy and medicine.

Call for Proposals

Princeton Precision Health Initiative announces the first call for research proposals

We are pleased to announce our first call for research proposals.
We currently have a focus in the following areas but will consider applications relevant to any interdisciplinary approaches to precision health:
Proposals for this call will be reviewed on a rolling basis until August 1, 2023.
To apply, please fill out the following form.
Recent Press

Princeton Precision Health: Using machine learning and data to improve health

highlight image

Princeton Precision Health’s goal is to take a comprehensive, data-driven approach to this type of health care challenge. Currently, researchers’ use of data is limited to the approaches specific to their discipline. Social scientists rarely include comprehensive genetic information in their work, and computational biologists rarely use social science data. Instead of working in silos, the initiative aims to bring experts from many fields together to collaborate on interdisciplinary data sets created with cutting-edge tools. Importantly, Troyanskaya said, ethical frameworks and behavioral modeling are integral to Princeton Precision Health’s approach to achieve effective and unbiased clinical outcomes and health policies.

Read the article from

Princeton Engineering

research image

Biomedical Science Advances

The data-driven methods that we develop are applied to the most pressing biomedical challenges, questions and technology. Our current emphases include maternal & fetal health, chronic kidney disease & diabetes, infectious, inflammatory & autoimmune diseases, neurodevelopment & mental health. We also welcome the opportunity to collaborate in other areas of impact.

research image

Clinical and Policy Impact

We apply the biomedical advances that our machine learning methods yield to develop strategies and drive policy for effective and equitable healthcare. At Princeton Prevision Health, data and machine learning scientists, biomedical researchers, psychologists, economists, social scientists, clinicians and policy experts, collaborate to produce equitable, effective, intelligent and precisely-targeted healthcare.

research image

Bias Reduction and Equity

Princeton Precision Health’s novel computational approach reveals patterns and insights not apparent with traditional research methods. This allows us to reduce human bias and shift paradigms. By challenging bias-based assumptions with data-driven, computationally-derived results, we aim to influence smart health policy and improve access to care across communities.

research image

Data Science and Machine Learning

We develop novel, computational, deep learning techniques specific to health-related challenges, which enable us to mine, analyze, and model data across currently siloed fields. Our methods utilize genomic, molecular, clinical, and socio-economic data as the ultimate integrator essential for providing effective, equitable health policy solutions.

Click here to learn more about our mission
News

NEWS ARTICLE

Princeton Precision Health: Using machine learning and data to improve health

Princeton Precision Health, a new University initiative, is taking on complex health care challenges using a data-driven, interdisciplinary approach.

Click here to read more

NEWS ARTICLE

Blood RNA alternative splicing events as diagnostic biomarkers for infectious disease

The role of RNA alternative splicing (AS) in Host-based response assays (HRAs) remains unexplored, as existing HRAs are restricted to...

Click here to read more

NEWS ARTICLE

Team of researchers led by Olga Troyanskaya discover sex-specific difference in immunity genes lead to worse COVID outcomes for men

A team of researchers from Princeton University, Flatiron Institute of the Simons Foundation, ....

Click here to read more

NEWS ARTICLE

Harnessing deep learning to find genetic causes of conditions such as autism

Prof. Troyanskaya at the World Economic Forum ...

Click here to read more

Events

PPH Fall Symposium

Sept. 29, 2023

Princeton University, Friend Center

Agenda to be announced

Click here to learn more.