Project Grant R21CA305472
- This Project Grant award, provided by the National Cancer Institute (CFDA 93.398 Cancer Research Manpower program), supports the development of an automated multimodal, multiscale algorithm for cervical cancer screening in low- and middle-income countries (LMICs). The $104,278 award, granted on January 11, 2026, will fund the following key objectives: Design a multimodal image registration algorithm to spatially correlate and combine information from widefield colposcope images and...
- The National Cancer Institute (NCI) has awarded a $572,490 Project Grant to The Regents of the University of California, San Francisco (UCSF) under the federal Cancer Detection and Diagnosis Research program (CFDA 93.394). The project, titled "PILLAR: Multi-Modal Imaging AI Models for Breast Cancer Risk", aims to develop an AI-powered tool to predict breast cancer risk using longitudinal data from mammograms, tomosynthesis, and MRI scans. The goal is to create more accurate cancer risk...
- This federal Project Grant award of $317,420 from the National Cancer Institute's Cancer Detection and Diagnosis Research program (CFDA 93.394) aims to develop and validate a patient-ready callascope device for cervical imaging and cancer prevention in low- and middle-income countries (LMICs). The primary focus is on creating point-of-care solutions for screening, diagnosis, and treatment that can be delivered by community health workers and midwives, thereby increasing access to care. Key...
- 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...
- 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...
- 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 Project Grant award from the National Cancer Institute (CFDA 93.394 - Cancer Detection and Diagnosis Research) in the amount of $399,112 will be used by Imvaria Inc. to adapt its fully automated, AI-powered "DigitalBX" diagnostic tool for analyzing chest CT scans to detect pulmonary nodules suspicious of lung cancer. The goal is to provide an end-to-end automated diagnostic solution implemented as a secure cloud-based application that is fully reimbursable, alleviating the cost...
- This federal Project Grant award of $505,613, provided by the National Cancer Institute (CFDA 93.394 Cancer Detection and Diagnosis Research), will support the development of statistical and computational approaches to harness genomic data and translate findings into precision prevention strategies for cancer. The key objectives are to: Develop deep learning-based methods to identify tumor subtypes linked to adverse outcomes and robust data integration approaches to assess associations between...
- 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...
- This Project Grant award from the National Cancer Institute (CFDA 93.393 - Cancer Cause and Prevention Research) provides $3,277,279 to Tufts Medical Center Parent, Inc. (doing business as Tufts Medical Center) to develop and evaluate English and Spanish smartphone Embodied Conversational Agents (ECAs) to improve follow-up rates for patients with abnormal cervical cancer screening results. The ECAs will provide follow-up recommendations, motivational interviewing, and facilitate communication...
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 genotyping, and AVE to improve cervical cancer detection and screening in regions with limited access to high-quality resources and personnel. The award period is from September 1, 2025 to August 31, 2027, and the work will be conducted by the University of Colorado-Denver.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $371.2k | 8/26/25 |