This Project Grant award from the National Cancer Institute (NCI), under the Cancer Detection and Diagnosis Research program (CFDA 93.394), provides $1,625,000.00 to Onc.ai, Inc. to develop and validate a radiomics-based multi-modal predictive model for metastatic non-small cell lung cancer patients treated with PD-1 immunotherapy. The key objectives are to: 1) Validate the predictive models in a multi-institutional prospective clinical study, 2) Evaluate the performance characteristics and...
The National Cancer Institute (NCI) awarded a $1,280,908 Project Grant under the Cancer Detection and Diagnosis Research program (CFDA 93.394) to Exai Bio Inc., a small disadvantaged business in Palo Alto, California. The grant supports the development of a novel assay and artificial intelligence (AI) model for early detection of non-small cell lung cancer (NSCLC) and predicting its subtypes using orphan non-coding RNA (oncRNA) biomarkers. The goal is to create a liquid biopsy-based diagnostic...
This National Cancer Institute (CFDA 93.394 Cancer Detection and Diagnosis Research) Project Grant award of $683,089 to the Sloan-Kettering Institute for Cancer Research supports the development of an improved, interpretable deep learning algorithm called DeepLIIF for more reproducible and accurate PD-L1 immunohistochemistry (IHC) biomarker quantification. The goal is to leverage virtual multiplex immunofluorescence (MPIF) restaining and large, diverse datasets across lung and bladder cancers to...
This $593,383 Project Grant, awarded by the National Cancer Institute under the Cancer Detection and Diagnosis Research program (CFDA 93.394), is supporting the development of an AI-augmented, multimodal, label-free nonlinear optical microscopy system for rapid and precise diagnosis of thyroid cancer and lymph node metastasis. The primary awardee, The Methodist Hospital Research Institute, is collaborating with The Johns Hopkins University on this project. The proposed system aims to eliminate...
This $700,611 Project Grant, awarded on March 11, 2025 by the National Cancer Institute (NCI) under the Cancer Cause and Prevention Research (CFDA 93.393) program, supports a practical randomized controlled trial (RCT) of artificial intelligence (AI) for melanoma diagnosis at Memorial Sloan Kettering Cancer Center (MSK) and Stanford University (SU). The goal is to determine the potential benefits and barriers to clinical adoption of AI-assisted dermoscopy, and to evaluate the impact on the...
This $989,122 Project Grant award from the National Cancer Institute (NCI) under the Cancer Detection and Diagnosis Research program (CFDA 93.394) aims to evaluate the performance of four commercial mammography-based artificial intelligence (AI) algorithms for breast cancer risk prediction in diverse U.S. screening populations. The project will assess the accuracy and equity of these AI risk models compared to traditional clinical risk factor-based models, using data from the Breast Cancer...
The National Institute of Biomedical Imaging and Bioengineering (NIBIB) has awarded a $693,156 Project Grant (CFDA 93.286 Discovery and Applied Research for Technological Innovations to Improve Human Health) to the Dana-Farber Cancer Institute, Inc. (DFCI) to develop artificial intelligence (AI) algorithms for predicting prognosis and optimizing treatment selection for cutaneous squamous cell carcinoma (CSCC), a highly prevalent form of skin cancer. The project aims to train and validate AI...
This Project Grant award from the National Cancer Institute's Cancer Detection and Diagnosis Research program (CFDA 93.394) provides $978,154 to Surgivance Inc. to further develop their digital pathology "laboratory-in-a-box" solution that rapidly produces and analyzes high-resolution, 3D digital pathology images for skin cancer detection at the point of care. The specific goals are to: 1) refine the AI algorithms for improved detection of basal and squamous cell carcinomas, 2) develop...
This federal Project Grant award of $718,456 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) supports research and development of an AI-powered system for automated analysis of abdominal CT scans to enhance detection and tracking of metastatic colorectal cancer. The key products and services to be delivered include: 1) Creating a large-scale...
This federal Project Grant award from the National Cancer Institute (NCI) under the Cancer Cause and Prevention Research program (CFDA 93.393) provides $1,043,109 to Isono Health, Inc. to develop and validate artificial intelligence (AI) models for its ATUSA 3D breast ultrasound imaging platform. The goal is to create lesion classification, lesion segmentation, and breast density calculator AI models to improve the ATUSA system's ability to accurately identify and diagnose breast cancer at an...