This National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) Project Grant award of $305,000 to Segmedix, CO. aims to develop an AI-powered software system to improve the accuracy, consistency, and efficiency of prostate cancer diagnosis using magnetic resonance imaging (MRI). The project will create a style-encoding generative adversarial network (GAN) to harmonize prostate MRI images from different scanner vendors and field strengths, and a transformer-based...
This $300,000 Project Grant awarded by the National Science Foundation (NSF) under the Integrative Activities (CFDA 47.083) program supports the development of an innovative, intelligent surgical probe for prostate cancer treatment. The project aims to create an edge artificial intelligence (AI) system-on-chip for bioimpedance analysis that can accurately distinguish cancerous from healthy tissue during prostate removal surgery. The novel technology being developed includes an adaptive filter to...
This Project Grant award from the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (CFDA 47.084) program provides $365,887 to The Research Foundation For The State University Of New York (RF SUNY) to develop an innovative artificial intelligence (AI) technology to select optimal treatment options for individual cancer patients. The goal is to prolong patient life by tailoring treatments to each patient, which can also reduce healthcare costs by avoiding...
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...
This $255,807 National Science Foundation project grant will fund the development of an AI-assisted software system to accelerate the labeling of medical tomographic images. Administered through the NSF Directorate for Engineering's Engineering program (CFDA 47.041), the grant aims to extract new information from medical images and improve patient outcomes. Alienbyte Scientific Software Inc. will apply machine learning algorithms to create an adaptive system that evolves to increase the speed,...
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 of $304,929.00 from the National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) program supports the development of new artificial intelligence (AI) models that utilize causal understanding and reasoning. The project aims to create a methodology for developing AI models that can provide reliable, traceable, and human-comprehensible analytics and decision-making for healthcare applications. The goal is to overcome the limitations of...
The National Science Foundation (NSF) awarded a $1,125,000 Project Grant to Case Western Reserve University's Office of Research Administration Division (doing business as University Hospitals of Cleveland) under the NSF's Computer and Information Science and Engineering (CFDA 47.070) program. The grant, awarded on September 1, 2023 and scheduled for completion on August 31, 2027, supports the development of an artificial intelligence-generated virtual contrast magnetic resonance imaging (MRI)...
This National Science Foundation (NSF) Project Grant award, under the Computer and Information Science and Engineering program (CFDA 47.070), provides $855,000 in funding to the Texas A&M Engineering Experiment Station (Tees) to develop a bimodal interpretable multi-instance medical image classification framework. The research aims to create a more scalable, interpretable, and robust artificial intelligence (AI) system to better analyze complex medical images, such as from multiple patient...
This Project Grant award of $499,997.00 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of a new framework to improve the interpretability and steerability of domain-specific AI models in medical imaging. The key products and services to be delivered include: Constructing an anatomically aware vision-language model capable of encoding and generating 3D medical images and radiology reports, to reduce the risk of...