Brief description not available

UCSF PIs developed a novel software platform for COVID-19 contact tracing and hotspotting called COVIDseeker. Covidseeker looks back in time and may be able to recreate people’s movements when infection rates were rising and falling in the spring and summer of 2020, giving epidemiologists an invaluable source of data as they try to predict what is going to happen in the fall and winter.This digital health invention has applications broader than COVID-19. The software can potentially be leveraged for other infectious diseases, treating obesity, and controlling smoking or alcohol addiction by showing where and when people are when they smoke, what are the triggers and how their location contributes to the risk of developing a particular disease.

The inventors have created a brain computer interface (BCI) that serves as a diagnostic and training tool of cognitive abilities and neural network function.

This invention is a novel technology developed to treat a patient’s neurological and/or psychiatric conditions. It consists of a system of implantable devices and computational algorithms that not only has autonomous control in sensing and stimulation of electrical signals in the patient’s brain, but also enables interactions with the external environment, thereby enhancing training and learning.

Modular Analysis of Genomic NETworks In Cancer (MAGNETIC) is a novel algorithm that performs functional network analysis of molecular profiling data to identify tumor biomarkers and link them to therapies.

This invention is a novel, automated method to rapidly detect and locate neurological emergencies such as acute intracranial hemorrhage on head computed tomography (CT) images using deep learning technology.

This invention can accurately and rapidly map patient bone structure and classify all tissue types such as fatty soft tissue, water soft tissue, lung tissue, bone, and air within a single scan using novel MRI acquisition and reconstruction techniques.

Brief description not available

Patients suffering from moderate to severe cardiac failure can enjoy substantial improvements in quality of life and survival, when provided with cardiac resynchronization therapy (CRT). However, this treatment has a 30% failure rate due in part to difficulties in characterizing intraventricular synchrony. Improvements in methodology could lead to appropriate patient selection and improved pacemaker positioning, resulting in enhanced therapeutic effectiveness. To redress these problems, UCSF researchers have developed software that permits the visualization and quantification of relevant parameters using a number of different imaging tools. Their novel method employs first harmonic imaging to the blood pool study, yielding a quantitative basis for treatment and evaluation.

The effective management of surgical operating rooms (OR) is crucial for safe, high quality, patient care. However, this can be very challenging due to the number of staff, patients, and rooms involved, combined with the necessary coordination of equipment, medications, and supplies. To address this important issue, the UCSF OR has developed a novel, easy to use tool to visualize and manage OR use in real-time.

UCSF investigators have designed a software package called DoseTailor that allows clinicians to use pharmacokinetically guided models to dose the chemotherapy agent docetaxel. DoseTailor can be easily expanded to include a wide variety of other antineoplasics including carboplatin, vinorelbine, ifosfamide, and 5-fluorouracil. Multiple models are available for use by the clinician, each with varying degrees of precision or error. Features of the software include automatic selection of the best precision model given the data available for an individual patient and a graphing function to allow visual assessment of the patients status within the dosing parameters. Both desktop Java-based and PALM-OS C-based applications are available for immediate use.