Project Grant R44CA285081
- This Project Grant award from the National Cancer Institute (NCI) under the Cancer Detection and Diagnosis Research program (CFDA 93.394) provides $978,154 to Surgivance Inc. to further develop a digital pathology "laboratory-in-a-box" solution that produces and analyzes high-resolution, 3D digital pathology images at the point of care within seconds. The solution combines rapid confocal imaging hardware with AI-enabled software to automatically recolorize and interpret the digital...
- 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...
- The National Cancer Institute (NCI) awarded a $591,468 Project Grant on August 6, 2025 under the Cancer Detection and Diagnosis Research program (CFDA 93.394) to The Research Foundation for the State University of New York (SUNY Oswego). The funding supports research to develop explainable machine learning models based on deep cancer pathophysiology to improve cancer diagnosis, risk stratification, and therapeutic recommendations. The project aims to address key gaps in integrating heterogeneous...
- This Project Grant award from the National Cancer Institute (CFDA 93.394 - Cancer Detection and Diagnosis Research) provides funding of $349,878 to the University of Utah to develop and test a novel electrical impedance dermography (EID) device augmented with machine learning (ML) capabilities. The project aims to assess the ability of the EID-ML technology to distinguish between different subtypes of basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), as well as differentiate...
- 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 Project Grant award of $306,798 from the National Cancer Institute (NCI) under the Cancer Detection and Diagnosis Research program (CFDA 93.394) aims to develop an artificial intelligence-based system to accurately identify malignant lymph nodes. The key objectives are to: Create a lymph node segmentation model to enable extraction of radiomic features critical for malignancy classification. Develop both cloud-based and standalone desktop deployment options for the classification model to...
- 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...
- This federal Project Grant award, valued at $306,872 and provided by the National Cancer Institute under the Cancer Treatment Research program (CFDA 93.395), aims to develop a new imaging system termed the Multi-Camera Array Scanner (MCAS). The MCAS will enable rapid 3D digitization and automated analysis of thick fine-needle aspiration (FNA) cytology smears, which are a critical first step in the cancer diagnosis pipeline. The project is a collaboration between Ramona Optics Inc., a small...
- The National Cancer Institute (NCI) awarded a $400,000 Project Grant under the Cancer Detection and Diagnosis Research program (CFDA 93.394) to Argosmd, Inc. to develop a low-cost, non-invasive Mini-Reflectance Confocal Microscopy (Mini-RCM) tool for aiding skin cancer diagnosis and treatment. The project aims to address limitations of existing Reflectance Confocal Microscopy (RCM) technology, which is FDA-cleared but has seen limited adoption due to high device cost, lack of portability, and...
- 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 Project Grant award from the National Cancer Institute (NCI), under the Cancer Detection and Diagnosis Research program (CFDA 93.394), provides $1,116,368 to develop a novel visualization, labeling, and tracking engine for human anatomy to enhance the standardization, precision, and communication of skin cancer data. The project aims to create methods to document reproducible and standardized anatomic site descriptions of skin cancer locations, visualize skin cancer locations, and attach data related to skin cancers at each affected anatomic site. This will facilitate communication between clinics, increase clinical accuracy and efficiency, and enhance patient safety by reducing the risk of wrong-site surgery for skin cancer. The project period is from Aug 1, 2025 to Jul 31, 2027, and the prime awardee is Am Operating LLC.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $1.1m | 7/29/25 |