Project Grant R01LM014163
- The federal Project Grant award of $1,602,000.00 from the National Institute of Environmental Health Sciences, under the Medical Library Assistance program (CFDA 93.879), will support the development of computational methods for analyzing multiplex immunofluorescence (MIF) imaging data to study the tumor microenvironment. The project aims to leverage a unique MIF dataset from over 2,000 cancer patients across 20 tumor types to develop innovative computational strategies, including spatial...
- This $240,000 federal Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) is supporting research at Yale University to develop new computational frameworks that combine large language models with neural operator learning techniques. The goal is to improve the ability to model and analyze spatiotemporal phenomena in biomedical research, such as tracking cellular and brain processes over time and...
- This $351,000 federal Project Grant award from the National Institute of Environmental Health Sciences (CFDA 93.879 - Medical Library Assistance) supports research to measure and improve the innovative potential of biomedical research and translation. The project develops computational, data, and network science tools integrated with a social science framework to analyze discovery and innovation dynamics, with the goal of accelerating transformative breakthroughs in biomedical fields. The...
- This federal Project Grant award of $376,184, provided by the National Institute of Environmental Health Sciences under the Medical Library Assistance program (CFDA 93.879), aims to investigate how integrating outside patient data into clinical workflows can improve healthcare outcomes and reduce costs. The key focus is on understanding how clinicians use data from health information exchanges (HIEs) and the value of that data for improving utilization, quality, and patient satisfaction. The...
- This National Science Foundation (NSF) Project Grant, awarded under the Computer and Information Science and Engineering program (CFDA 47.070), provides $220,000 to Yale University from September 1, 2023 through August 31, 2027. The project aims to develop a smarter artificial intelligence (AI) system to better understand and analyze complex medical images, such as those from multiple scans of a patient. The research team will tackle challenges to make the AI system more scalable, interpretable,...
- This Project Grant award, in the amount of $249,000.00, was provided by the National Institute of Environmental Health Sciences under the Medical Library Assistance federal grant program (CFDA 93.879). The objective of this 3-year project is to develop a novel Contrastive Feature Analysis (CFA) framework to improve the transparency and performance of deep neural networks for medical image analysis. Key deliverables include: 1) Developing an efficient CFA visualization technique to quantify the...
- This federal Project Grant award of $460,740 from the National Institute of General Medical Sciences (NIGMS) under CFDA 93.859 (Biomedical Research and Research Training program) will support research by Yale University to develop scalable methods for inferring the most important interactions within large biological networks. The goal is to investigate two model systems: (i) neural activity and (ii) chromatin structure, in order to identify the networks of interactions that best describe...
- This federal Project Grant award of $1,396,731.00 from the National Institute of Environmental Health Sciences (NIEHS), under the Medical Library Assistance (CFDA 93.879) program, aims to develop a computational framework for the quality assessment and curation of biological models. The primary objectives are to standardize and automate the iterative process of assembling, documenting, verifying, and validating models of cell signaling. This will maximize the accuracy and reuse potential of...
- This federal Project Grant award of $426,479 from the National Institute of General Medical Sciences (NIGMS), under the Biomedical Research and Research Training program (CFDA 93.859), will support research toward developing statistical and computational tools to enable precision risk stratification, diagnosis, and treatment of medical conditions. The research will focus on integrating and synthesizing data from diverse sources such as biobanks, electronic health records, and clinical registries...
- This federal Project Grant award of $402,750 from the National Institute of Environmental Health Sciences under the Medical Library Assistance program (CFDA 93.879) supports the development of large language models (LLMs) for drug safety and effectiveness causal analysis using real-world data from electronic health records (EHRs). The primary objective is to build an LLM-based causal analytical platform that can robustly determine a wide variety of clinical phenotypes, including those not...
The federal Project Grant award of $2,720,667 from the National Institute of Environmental Health Sciences (CFDA 93.879 - Medical Library Assistance) will fund research at Yale University to develop robust algorithms and a tool to help clinicians and life scientists better understand the estimates of predictive models by visualizing patient neighborhoods based on supervised weighted distances. The goal is to increase trust in complex, multivariate predictive models used in clinical AI and allow for proper application to data from clinicians' own patients. The research will explore how context-based visualizations can work for deep neural network models using real-world data, and develop privacy-protecting versions of the algorithms that can work with federated databases. The award period runs from September 17, 2025 to August 31, 2029.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $2.7m | 9/17/25 |