Project Grant R01CA296388
- This $256,000 National Science Foundation Project Grant under the Engineering (47.041) program will support the development of an artificial intelligence-based system for analyzing multiparametric magnetic resonance imaging (MRI) scans to detect prostate lesions. The awardee, Taurus Diagnostics, Inc., will create a novel prostate cancer diagnostic platform leveraging artificial intelligence image analysis for high sensitivity and specificity. Key objectives include developing methods to...
- The National Cancer Institute awarded a $717,667 Project Grant titled "Artificial Intelligence Enabled Stroma-Weighted Automated Grading System to Improve Risk Stratification in Black Men" under the Cancer Detection and Diagnosis Research program (CFDA 93.394). The grant aims to develop an AI-enabled automated grading system that leverages multiphoton microscopy and second harmonic generation imaging to analyze prostate cancer tumor biology and improve risk stratification, particularly...
- The U.S. National Cancer Institute (NCI) awarded a 5-year, $680,433 Project Grant to the University of California, San Francisco (UCSF) under the NCI's Cancer Detection and Diagnosis Research (CFDA 93.394) program. The grant supports research aimed at using cutting-edge spatial proteogenomic technologies and pathology artificial intelligence (PAI) to improve prognostic estimation and elucidate the underlying biology driving PAI outcomes in prostate cancer. The project seeks to: 1) understand the...
- This federal Project Grant award from the National Cancer Institute (CFDA 93.394 - Cancer Detection and Diagnosis Research) provides $603,981 to the University of Wisconsin-Madison to conduct research on integrated clinical-grade genomic and pathology artificial intelligence (AI) biomarkers for high-risk prostate cancer. The key objectives are to: 1) validate genomic and pathology AI as prognostic biomarkers for high-risk prostate cancer patients; 2) validate genomic and pathology AI as...
- This federal Project Grant award from the National Institute of Biomedical Imaging and Bioengineering (NIBIB), under the Discovery and Applied Research for Technological Innovations to Improve Human Health program (CFDA 93.286), aims to improve the diagnostic accuracy and cost-effectiveness of breast cancer screening through the development of an AI system. The $672,087 grant, awarded on August 12, 2025, will fund a research project at New York University School of Medicine to build a...
- The University of Delaware (UDE) has been awarded a $245,087 Project Grant from the National Cancer Institute (CFDA 93.394 - Cancer Detection and Diagnosis Research) to develop advanced AI-assisted prostate MRI interpretation capabilities. The project, titled "Integrating Radiologist Insights for Safe and Accurate AI-Assisted Prostate MRI Interpretation", aims to build on prior breakthroughs in image processing and natural language processing to create new AI tools for interpreting...
- This Project Grant award from the National Cancer Institute (CFDA 93.394 - Cancer Detection and Diagnosis Research) provides $371,161 to develop advanced AI-based risk models for cervical cancer screening in low-resource settings. The project aims to leverage time-series imaging data and self-supervised learning to enhance the diagnostic accuracy of automated visual evaluation (AVE) models. The goal is to create a comprehensive risk stratification system that combines imaging data, HPV...
- The University of Michigan has been awarded a $568,151 Project Grant from the National Cancer Institute (CFDA 93.394 - Cancer Detection and Diagnosis Research) to develop a real-time functional imaging platform for accurate diagnosis and prognosis of prostate cancer. The project aims to leverage photoacoustic imaging and biocompatible hydrogel nanoparticle probes to quantitatively assess prostate gland microarchitecture and tumor microenvironment as imaging biomarkers for improved prostate...
- The National Cancer Institute (NCI) awarded a $700,611 Project Grant under the Cancer Cause and Prevention Research program (CFDA 93.393) to the Sloan-Kettering Institute for Cancer Research. The grant, titled "Practical Randomized Controlled Trial of Artificial Intelligence for Melanoma Diagnosis (PRACTA-MEL)," aims to determine the benefits and barriers to clinical adoption of AI systems for improving melanoma detection and reducing the number of unnecessary biopsies. The project...
- This $435,827 Project Grant from the National Cancer Institute (NCI) under the CFDA 93.394 Cancer Detection and Diagnosis Research program supports research conducted by New York University (NYU) School of Medicine to develop deep learning methods for analyzing mass spectrometry imaging (MSI) data. The goal is to make MSI data more accessible to existing machine learning workflows by expanding the dimensionality of the data structure to treat each metabolite or lipid as an individual "color...
This $681,215 federal Project Grant was awarded on September 1, 2025 by the National Cancer Institute (CFDA 93.394 - Cancer Detection and Diagnosis Research) to New York University (NYU) to develop AI-powered diagnostic tools for early prostate cancer detection. The project aims to leverage machine learning models to infer the presence of clinically significant prostate cancer using a minimal amount of degraded MRI data, in order to enable widespread, cost-effective population-level disease surveillance. The 5-year project seeks to democratize MRI-based diagnostics and improve upon the current standard-of-care, the prostate-specific antigen (PSA) test, which has low specificity leading to unnecessary advanced imaging and invasive procedures. By developing an AI-powered, MRI-based approach that can operate with limited data, the project has the potential to significantly enhance early prostate cancer detection and clinical outcomes at the population level.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $681.2k | 8/28/25 |