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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.

Magnetic: A Novel Algorithm for Identification of Cancer Therapeutics

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.

System And Method For Rapid Automated Head Computed Tomography Analysis

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.

Novel Software for Generating Attenuation Correction Maps with MRI for PET Reconstruction

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.

Decoding Speech Sounds From The Human Brain For A Communication Neuroprosthetic Device

Speech requires the precise movement of the lips, tongue, and jaw in order to produce the wide variety of sounds that comprise any given language.  These movements are controlled by a small region on the surface of the brain known as the ventral sensorimotor cortex (vSMC).                 Certain neurodegenerative disorders such as Lou Gehrigs’s disease/ALS or multiple sclerosis, along with paralysis due to injury or stroke, can leave individuals unable to speak due to their inability to move the required muscles.  In many of these cases, the patients still retain the cognitive ability to compose speech and visualize the muscle movements required to generate that speech.  This inability to communicate is particularly acute for a subset of patients suffering from locked-in syndrome (LIS).  These individuals are fully conscious but are only, at best, able to move their eyes.  The inability of these patients to effectively communicate is compounded by the fact that stroke-related LIS has 5- and 10-year post-onset survival rates of over 80% [1].  Various speech generating devices have been developed to assist LIS patients and others with severe motor-related speech defects.  However, none of these devices have been able to offer efficient communication since they are limited by the speed at which patients can select individual letters and/or words by movement of a finger or an eye.   Despite these limitations, the market for speech generating devices is projected to grow to $505M by 2018.

Methodology to Measure Transvalvular Energy Loss Using Doppler Echocardiography

In patients with stenosed heart valves, hemodynamic performance of the heart valve is routinely assessed to determine risk stratification and timing of intervention. Hemodynamic performance is also used to evaluate the success of a valve transplant and monitor the performance of the valve over time. Current measures of hemodynamic performance include measures of transvalvular pressure gradient, effective orifice area, and blood flow velocity.  These common criteria only allow assessment of forward flow and do not take into account paravalvular leak and paravalvular regurgitation (backward flow). Leak and regurgitation are commonly seen in stenosed valves, deformed prostheses, and particularly in transcatheter valves. Assessment of valvular hemodynamics during both forward and backward flow would improve risk stratification of patients and timing of interventions.      Valve hemodynamics during both forward and backward flow can be assessed by measuring energy loss. Until now, routine clinical application of energy loss measurement has been hindered by its invasive nature and a lack of simple tools to obtain the data. Energy loss measurement currently requires catheterization and placement of pressure transducers inside the artery on opposite sides of the valve in question.  A non-invasive and simple way to measure energy loss would provide clinicians with a tool to improve assessment of hemodynamics and improve patient care.     


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.

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