Researchers at the National Institute on Drug Abuse (NIDA) seek licensing or co-development of a mobile health technology that monitors and predicts a user’s psychological status in order to deliver an automated intervention when needed.
Available for licensing is computer software for the automated generation of density maps of macromolecular structures from a series of 2D digital micrographs of frozen hydrated specimens collected using an electron microscope equipped with an ultra-cooled computerized stage.
This invention pertains to a system for continuous observation of rodents in home-cage environments with the specific aim to facilitate the quantification of activity levels and behavioral patterns for mice housed in a commercial ventilated cage rack. The National Cancer Institute’s Radiation Biology Branch seeks partners interested in collaborative research to co-develop a video monitoring system for laboratory animals.
Researchers at the National Institute on Drug Abuse (NIDA) seek licensing or co-development of a Human Research Information System (HuRIS) software that automates all major functions of a clinical-research entity. The system is designed for commercial healthcare providers, community treatment centers, and clinical research facilities.
Researchers from NCI and Rudgers University developed methods of detecting abnormal cells in a sample using the spatial position of one or more genes within the nucleus of a cell, as well as a kit for detecting abnormal cells using such methods. The invention also provides methods of identifying gene markers for abnormal cells using the spatial position of one or more genes within the nucleus of a cell.
The National Cancer Institute seeks parties interested in collaborative research to co-develop diagnostic methods for detection of cancer using spatial genome organization.
Researchers at the National Institutes of Health Clinical Center (NIHCC) developed a technology that improves segmentation detail levels for anatomical structures in medical images through a new, deep learning approach. Difficult anatomical features, often segmented incorrectly with other image segmentation methods, are correctly segmented and identified using this novel technology, which is available for licensing or co-development.
The National Institute on Drug Abuse (NIDA) seeks licensing and/or co-development research collaborations for use of software for substance use disorders, behavior modification, and cancer patient care and pain management, etc. NIDA has developed software that permits real-time communication of patient-reported data and associated geolocation data. The software can be used in patient treatment or as a research tool for evaluating effectiveness of treatments.
The National Institutes of Health - Clinical Center (NIH-CC) seeks to license and/or co-develop methods of reading chest x-rays using a deep learning models to detect a disease and describe its contents.
The National Cancer Institute (NCI) seeks research, co-development, or licensing partners for software that uses computational approaches in cancer diagnosis. NCI researchers have recently developed a computational approach for detecting, quantifying, and mapping Mitotic Hotspots in whole slide images of tumor tissue. This technology has demonstrated high reproducibility that is unaffected by diagnostic skill or fatigue, allowing standardization of tumor cell proliferation assessment across institutions.
National Cancer Institute (NCI) researchers have developed a novel software tool for uniform recording of Mitotic Figure (MF) counts via conventional and/or digital microscopy. With this technology, diagnostic centers can standardize electronic recording, summation, and transcription of clinical data during surgical pathology examination. NCI seeks licensing partners to further develop this application for use in diagnosis and detection of malignant cancers.
Scientists at The National Cancer Institute (NCI) and The National Institute of Neurological Disorders and Stroke (NINDS) have invented a method of imaging glucose metabolism in vivo using MRI chemical shift imaging (CSI) experiments that relies on a simple, but robust and efficient, post-processing procedure by the higher dimensional analog of singular value decomposition, tensor decomposition. This new technology is denoising software for MRIs that significantly improves the measurement of low-intensity signals without the need for dynamic nuclear polarization (DNP). The scientists seek research co-development partners and/or licensees for their invention.