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You are here: Home / Archives for Karen

S.F. composers meld sound with science for new perspective on Alzheimer’s

S.F. composers meld sound with science for new perspective on Alzheimer's
Source: CBS News
February 24, 2023

Srikantan Nagarajan, UCSF BCHSI faculty / neuroscientist, provided data to young composers.

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Yau, Christina

February 23, 2023 By Karen

Christina Yau, PhD

Developing biomarker-informed patient-centered clinical trial designs to improve outcomes and minimize toxicity

My research focuses on identifying predictive biomarkers of response and refining clinical trial endpoints. The goal is to develop patient-centered, biomarker-informed clinical trial designs to identify novel regimens that improve outcomes while minimizing toxicity for early stage breast cancer patients.

UCSF, Stanford researchers predict newborn health outcomes using AI, EHR data

UCSF, Stanford researchers predict newborn health outcomes using AI, EHR data
Source: Becker's Healthcare
February 16, 2023

Marina Sirota, UCSF BCHSI and Stanford collaborators publish in Science Translational Medicine.

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Ntranos, Vasilis

February 14, 2023 By Karen

Vasilis Ntranos, PhD

Computational methods development at the intersection of information theory, genomics, and machine learning

Our research revolves around key algorithmic and statistical challenges that arise in computational biology, with a particular focus on variant effect prediction and single-cell genomics — and is highly collaborative, spanning multiple biological domains in immunology, human genetics, and cancer biology.

Ge, Jin

February 14, 2023 By Karen

Jin Ge, MD, MBA

Electronic Interventions to Improve the Care of Patients with Chronic Liver Diseases and Cirrhosis

Dr. Ge’s research focuses on using clinical informatics, data science and artificial intelligence to improve the quality of care for patients with advanced liver diseases and awaiting transplant.

High Honors for Outstanding Science Contributions

Atul Butte, MD, PhD
Source: UCSF
January 31, 2023

Atul Butte is named 2022 fellow by the American Association for the Advancement of Science.

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Gennatas, Efstathios

February 2, 2023 By Karen

Efstathios D. Gennatas, MBBS, PhD

Advanced and Accessible Health Data Science for All

Dr. Gennatas has developed rtemis, a comprehensive data science platform, which supports advanced visualization, statistical analyses, and machine learning. It provides both a highly flexible and efficient API as well as a no-code web application to bring advanced data science tools to biomedical researchers and clinicians regardless of technical expertise.

Big Little Lives

Marina Sirota, PhD
Source: UCSF Magazine
Winter 2023

Bakar faculty Marina Sirota et al microbiome work highlighted in the context of pregnancy outcomes.

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Alaa, Ahmed

January 23, 2023 By Karen

Ahmed Alaa, PhD

Machine learning for Cardiology

Developing machine learning models for multi-modal data to predict cardiovascular disease risk and response to therapy.

Yala, Adam

November 29, 2022 By Karen

Adam Yala, PhD

Machine Learning for Precision Oncology: Algorithms for Multi-modal Inference and Policy Design

The Yala lab develops machine learning models for personalized care and translates them to clinical practice. It focuses on designing modeling approaches that are robust to data-generation biases, offer mechanisms for clinical deployment and can adapt to diverse clinical requirements.

Yang, Yang

November 3, 2022 By Karen

Yang Yang, PhD

“Push and go CMR”: comprehensive and free-breathing AI-powered cardiac magnetic resonance imaging

This project aims to improve the throughput by automated rapid scanning with minimal input from technicians and improve patient comfortableness with an ECG-free and free-breathing scan procedure with self-navigation powered by an inline AI framework.

Travel time to abortion facilities grew significantly after Supreme Court overturned Roe v. Wade

Graph of travel time to get to abortion by state
Source: JAMA
November 1, 2022

Bakar faculty, senior author Yulin Hswen publishes on abortion access post: Dobbs v Jackson Women’s Health Decision.

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Win NIH High-Risk, High-Reward Research Grant

Photo of Hani Goodarzi
Source: UCSF SOM
October 31, 2022

Bakar faculty Hani Goodarzi receives the NIH Director’s Transformative Research Award.

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2 BCHSI Faculty Elected to the National Academy of Medicine for 2022

Photo of Ida Sims and Katie Pollard
Source: UCSF
October 17, 2022

Two Bakar Faculty – Ida Sim and Katie Pollard are among the 3 elected.

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Scientists show how EMR may be used to learn more about Alzheimer’s disease

Scientists show how EMR may be used to learn more about Alzheimer’s disease
Source: NIA NIH
September 22, 2022

The NIA NIH highlighted work by BCHSI faculty lead Alice Tang, Sirota Lab and Information Commons team.

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Rauschecker, Andreas

September 15, 2022 By Karen

Andreas M. Rauschecker, MD, PhD

Digital and Computational Health Science

Dr. Rauschecker’s lab leverages modern AI methodologies to quantify, describe, and understand clinical brain MRIs. This work includes new imaging biomarker discovery, using AI for diagnostics and prognostics, and using AI for better understanding variation in the normal brain.

Joint Computational Health PhD Program Opens Applications Today

Source: UC Berkeley
September 15, 2022

Program is administered in partnership with the Division of Computing, Data Science, and Society at Berkeley and UCSF BCHSI.

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UCSF AI4ALL Summer 2022 Wraps Up with Final Symposium

UCSF AI4ALL Summer 2022 Wraps Up with Final Symposium
Source: BCHSI
September 8, 2022

29 talented high school students learned about AI applications in biomedicine.

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De-ID Clinical Notes Scale Project Wins Golden Sautter Award

De-ID Clinical Notes Scale Project Wins Golden Sautter Award
Source: UCOP
August 17, 2022

BCHSI faculty gain highest UC Tech award honor for Deidentifying Clinical Notes at Scale.

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March of Dimes Launches New Data-Focused Prematurity Research Center at UCSF

March of Dimes Launches New Data-Focused Prematurity Research Center at UCSF
Source: March of Dimes
June 23, 2022

BCHSI faculty Marina Sirota et al will focus on data sharing, computational drug discovery, leveraging real world data to help prevent preterm birth.

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New Biomarker Classifications May Improve Treatment for High-Risk Breast Cancer Patients

New Biomarker Classifications May Improve Treatment for High-Risk Breast Cancer Patients
Source: UCSF
June 3, 2022

BCHSI faculty Laura van’t Veer & team findings will guide treatment prioritization.

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Peterson, Thomas

June 2, 2022 By Karen

Thomas A. Peterson, PhD

Digital and Computational Health Science

Application of statistical and computational methodologies to prospective and retrospective clinical datasets for finding meaningful statistical associations and creating state-of-the-art tools for precision medicine

Two Artificial Intelligence / Machine Learning Demonstration Projects Awarded

Two Artificial Intelligence / Machine Learning Demonstration Projects Awarded
Source: Bakar Institute
May 31, 2022

BCHSI, CTSI and UC Health award two AI/Machine Learning Demo Pilot projects.

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Towards Continual Monitoring & Updating AI algorithms in Healthcare

Towards Continual Monitoring & Updating AI algorithms in Healthcare
Source: Nature
May 31, 2022

Jean Feng, Romain Pirracchio, et al published on Quality Improvement for Clinical AI.

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UCSF Awarded $67.5 Million to Develop New Antiviral Therapies

UCSF Awarded $67.5 Million to Develop New Antiviral Therapies
Source: UCSF
May 18, 2022

BCHSI Faculty, Andrej Sali, Brian Shoichet, Michael Keiser, are investigators for this QBI Coronavirus Research Group.

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Informations Commons Day at UCSF

UCSF Information Commons Day
Source: Bakar Institute
April 28, 2022

As researchers who depend on data, join us on Monday, May 9 to learn how to deepen your research inquiry.

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UCSF Researchers Use Gene Expression Data to Map Cell Types in the CNS

UCSF Researchers Use Gene Expression Data to Map Cell Types in the CNS
Source: Bakar Institute
April 12, 2022

Ashish Raj co-led the development of a computational pipeline, Matrix Inversion and Subset Selection.

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Single-Cell Seq Study Uncovers Blood Cell Type Features for Lupus

Single-Cell Seq Study Uncovers Blood Cell Type Features for Lupus
Source: Science
April 8, 2022

Jimmie Ye, et al, published in Science on how they deployed mux-seq to profile 1.2M immune cells for lupus.

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Olshen, Adam

April 8, 2022 By Karen

Adam B. Olshen, PhD

Developing tools for the analysis of genomic data and identifying biomarkers in cancer

Dr. Olshen has helped develop tools in such area as DNA copy number, mutation hotspot detection, and integration of data from multiple genomic assays. He is currently developing biomarkers to predict cancer outcomes in pediatric cancers.

A Biomedical Open Knowledge Network Harnesses the Power of AI

A biomedical open knowledge network harnesses the power of AI
Source: AI Magazine
March 31, 2022

Sharat Israni, et al and collaborators publish on knowledge networks identified by NSC as a core component of AI frameworks.

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Rudrapatna, Vivek

January 10, 2022 By Karen

Vivek Rudrapatna, MD, PhD

The Real-World Evidence Laboratory

Our group uses a variety of machine learning and biostatistical methods, such as natural language processing, deep learning, and causal inference, to transform electronic health records data into real-world evidence on treatment effects.

Atul Butte Testifies before Congress

Atul Butte Congressional Testimony
Source: Bakar Institute
December 8, 2021

Butte articulated priorities to Energy & Commerce Subcommittee on Health “Future of Biomedicine” Hearing.

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An Entirely New Approach to Drug Discovery for AD

An Entirely New Approach to Drug Discovery for AD
Source: Bakar Institute
November 17, 2021

UCSF BCHSI data scientist’s research draws attention to an entirely new approach to drug discovery for Alzheimer’s.

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Precision Medicine to Address Prostate Cancer in Veterans

Franklin Huang, MD, PhD
Source: Bakar Institute
November 16, 2021

Franklin Huang: Providing precision oncology solutions for veterans using data science and focusing on disparities.

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Could an antidepressant prevent more COVID deaths?

Could an antidepressant prevent more COVID deaths?
Source: UCSF
November 15, 2021

A UCSF-Stanford data analysis shows a strong association between taking SSRIs and surviving the virus.

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Lazar, Ann

November 3, 2021 By Karen

Ann A. Lazar, PhD

Biostatistics, Data Science and Precision Health

Dr. Lazar’s research focuses on biostatistics, data science and precision health. She has secured grant funding as PI from NIH, foundations and the University of California Office of the President, including grants for the HBCU initiative.

Computational Precision Health Program Funded by $50M Gift Launches

Ida Sim, MD, PhD
Source: UCSF
October 20, 2021

Ida Sim, MD, PhD and new UCSF program faculty will be affiliated with the BCHSI.

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Disparities Research in Chronic Diseases with $22.5M Grant

Stuart Gansky, MS, DrPh and William Brown III, PhD, DrPH
Source: UCSF
October 18, 2021

Stuart Gansky, MS, DrPh, co-director, and William Brown III, PhD, DrPH as associate unit director.

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Can an Already Approved Drug Treat Alzheimer’s Disease?

Marina Sirota, PhD
Source: Gladstone Institutes
October 11, 2021

Marina Sirota, PhD (co-senior author) published a study using computation to pinpoint an existing drug that may prevent Alzheimer’s Disease.

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Operational Excellence

Operational Excellence

August 31, 2021 By Karen

Optimize and sustain delivery of BCHSI programs and services through implementation of best practices that promote efficiency, effectiveness, and quality.

Policy & Advocacy

Policy & Advocacy

August 31, 2021 By Karen

Champion the benefits and potential impact of computational health sciences; advocate priorities to advance the field; and promote data-driven solutions to key challenges faced by UCSF, UC Health and the […]

Training

Training

August 31, 2021 By Karen

Train and educate innovators and thought leaders in computational health sciences at UCSF.

People

August 31, 2021 By Karen

Attract, nourish and retain the best talent, reflecting the rich diversity of our global community, to enable research in UCSF departments while providing a home to data-driven thought leaders and […]

Knowledge Assets

Knowledge Assets

August 31, 2021 By Karen

Develop and enable safe and respectful access to the latest AI tools and relevant data assets of interest to all researchers in UCSF and beyond, while remaining attentive to social […]

Research

Research

August 31, 2021 By Karen

Build and apply tools and methods in computational science to advance the field and support research in biomedical disciplines, with a focus on advancing equitable precision medicine.

UCSF SPOKE featured at NSF Convergence Accelerator Expo

Source: Bakar Institute
July 6, 2021

Learn about UCSF’s knowledge network project and other innovative work supported by NSF Convergence Accelerator.

Watch Video

AIMBE honors two Bakar Faculty

AIMBE
Source: Bakar Institute
March 19, 2021

Katie Pollard and Duan Xu are inducted into the prestigious American Institute for Medical and Biological Engineering College of Fellows.

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Kornblith, Aaron

February 12, 2021 By Karen

Aaron Kornblith, MD

Accurate and Consistent Advanced Diagnostic Strategies for Injured Children

Dr. Kornblith is focused on novel diagnostic strategies to enhance the care of injured children. He uses
a modern data science framework to develop accurate, consistent, and interpretable advanced analytic
models for rapid detection of intra-abdominal bleeding using clinical decision rules, computer vision,
and device design.

Fragiadakis, Gabriela

February 10, 2021 By Karen

Gabriela K. Fragiadakis, PhD

Characterizing immune organization and patient immune state using single-cell methods

Dr. Fragiadakis’s research focuses on analyzing immune state in diverse sets of patient cohorts using high-dimensional single-cell technologies, including single-cell sequencing and CyTOF. She uses multi-modal data integration methods to evaluate patient differences and infer broader principles of immune organization.

Semere, Wagahta

February 10, 2021 By Karen

Wagahta Semere, MD, MHS

Promoting Quality and Safety by Engaging Diverse Diabetes Patients and their Caregivers in Secure Messaging

Dr. Semere is using machine learning and novel computational linguistics techniques to characterize secure message communication between racially/ethnically diverse patients with diabetes, their caregivers, and providers. She is applying this information to develop family-centered technology based communication strategies that promote effective diabetes management.

Spitzer, Matthew

February 2, 2021 By Karen

Matthew H. Spitzer, PhD

Systems approaches to understand immune responses, particularly to cancer

We focus on understanding how the immune system coordinates responses with an emphasis on tumor immunology. We combine experimental and computational methods to understand how the immune system responds to tumors and to rationally initiate curative immune responses against cancer.

Feng, Jean

February 2, 2021 By Karen

Jean Feng, PhD

Developing reliable and interpretable machine learning algorithms for clinical decision making

Dr. Feng has developed machine learning and deep learning algorithms that accurately quantify their uncertainty and are appropriate for high dimensional datasets. Her current research is in developing safe machine learning algorithms that learn and recalibrate using streaming Electronic Health Records data.

Wesson, Paul Douglas

February 2, 2021 By Karen

Paul Douglas Wesson, PhD

The science for the last mile: Enhanced epidemiologic surveillance to accelerate HIV elimination

The objective of this NIAID-funded K01 award is to identify the residual drivers of HIV infection in Fast Track cities. Methods from semi-parametric
statistical modeling, HIV phylogenetics, and minority stress theory will be used to augment surveillance data.

Spetz, Joanne

December 16, 2020 By Karen

Joanne Spetz, PhD

Health workforce and the organization and delivery of healthcare services

Dr. Spetz uses econometric and mixed methods to study the organization of the health workforce and delivery of healthcare services, primarily with large secondary and survey-based datasets.

Sarkar, Urmimala

December 16, 2020 By Karen

Urmimala Sarkar, MD, MPH

Innovating for Health Equity

Dr. Sarkar’s research focuses on: (1) Ambulatory patient safety, (2) Digital health innovations to improve the safety and quality of outpatient care, (3) Social media research for behavior change, (4) Safety-net implementation of evidence-based digital health in real-world settings.

Hswen, Yulin

September 2, 2020 By Karen

Yulin Hswen, ScD

Social and Computational Epidemiology

Dr. Hswen current research seeks to identify authentic attitudes, feelings and beliefs that influence behaviors and drive populations. Through the collection of unconventional and underground online social networks, Dr. Hswen captures unfiltered conversations to further understand the connections between social experiences and health.

Yao, Keluo

September 2, 2020 By Karen

Keluo Yao, MD

Improving Research and Operational Software for Laboratory Medicine

Pathology and laboratory medicine provide 70% of the information in most patient care settings. Therefore, using the best software is the best way to deliver that information to the clinicians on the front lines. I am interested in developing these software solutions by utilizing the best practices from the cutting edge artificial intelligence technologies to traditional methods.

Ushizima develops image recognition algorithms to diagnose COVID-19

Daniela Ushizima develops image recognition algorithms to diagnose COVID-19
Source: BERKELEY LAB COMPUTING SCIENCES
June 1, 2020

Dani Ushizima explores algorithms and a data analysis pipeline to help accurately distinguish COVID-19 abnormalities in CT scans and chest X-rays.

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UCSF and AWS Collaboration

UCSF & AWS Collaboration
Source: Bakar Institute
May 12, 2020

Facilitated by BCHSI, AWS connected with the laboratory of Charles Chiu to enable two COVID-19 projects.

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Ushizima, Daniela

April 16, 2020 By Karen

Daniela Ushizima, PhD

Algorithms for Multimodal and N-Dimensional Imaging Experiments

Dr. Ushizima research focuses on computer vision algorithms for monitoring diseases progression while exploring information from multiple imaging techniques. Together with Grinberg’s lab, developed quantitative histological analysis of whole human brains using multiple instruments.

UC Health Data Initiative Launches Daily Updates on COVID-19 Tests

Source: University of California
April 6, 2020

UC Health will distribute daily updates about SARS-CoV-2 testing volume, the # of positive tests & age distribution of confirmed cases gathered from its 5 medical centers.

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Bakar Institute Develops COVID-19 County Tracker App

COVID-19 County Tracker
Source: Bakar Institute
APRIL 3, 2020

Butte lab developed a COVID-19 County Tracker app to track cases nationwide. It features plots of total cases by states and county, with interactive exploration.

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Acid Reflux Drug Is a Surprising Candidate to Curb Preterm Birth

Acid Reflux Drug Is a Surprising Candidate to Curb Preterm Birth
Source: UCSF
February 13, 2020

Marina Sirota uses a computational study to identify a dozen of other drugs to reduce inflammation.

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Jiang, Fei

January 14, 2020 By Karen

Fei Jiang, PhD, MS

High quality statistical and computational publications focusing on addressing practical problems in the medical domain

Dr. Jiang’s research interest lies in machine learning methods, high dimensional models, functional data analysis and their applications in analyzing neurological, image, genetics data, and in designing adaptive randomization clinical trials. Her efforts yield high quality statistical and computational publications, which focus on addressing practical problems in the medical domain.

Scheffler, Aaron

January 14, 2020 By Karen

Aaron Scheffler, PhD, MS

Analysis of complex datasets to better understand biological systems and inform meaningful clinical decisions

Dr. Scheffler develops statistical methods for high-dimensional signals produced by his collaborators in neurology and orthopedics. The proper interrogation of this data will lead to improved health outcomes at both the patient and population level.

Abbasi-Asl, Reza

January 14, 2020 By Karen

Reza Abbasi-Asl, PhD

Interpretable machine learning to understand brain functions and related disorders

The Abbasi Lab aims to understand functions of the brain and related disorders by leveraging principles in machine learning and statistics. The lab studies large-scale single-cell level neurophysiological datasets as well as medical images and structured and unstructured healthcare data.

BCHSI Faculty Named on Forbes’ 30 under 30

Forbes' 30 Under 30
Source: UCSF
DECEMBER 10, 2019

Vijay Ramani has been named to Forbes magazine’s annual 30 Under 30 list of rising stars in healthcare.

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Unprecedented Partnership to Advance Data in Biomedicine

Baranzani and Israni lead the NSF Award
Source: UCSF Precision Medicine
November 7, 2019

Sergio Baranzini and Sharat Israni will lead the NSF award & collaborate with Google, Lawrence Livermore Library, and Institute Systems for Biology.

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Data Science Health Innovation Fellows announced

Data Science Health Innovation Fellows
Source: Bakar Institute
November 4, 2019

BCHSI and BIDS welcome the 2019 Data Science Health Innovation Fellows.

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Julia Adler-Milstein Elected to the National Academy of Medicine for 2019

Julia Adler-Milstein Elected to the National Academy of Medicine for 2019
Source: UCSF
October 21, 2019

Four UCSF faculty members are among the 100 new members elected to the National Academy of Medicine this year, including BCHSI affiliate faculty Julia Adler-Milstein.

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Lyles, Courtney

October 18, 2019 By Karen

Courtney Lyles, PhD

Reinforcement Learning Algorithm for Motivating Physical Activity among Patients with Diabetes and Depression

We are developing & testing smartphone apps that use reinforcement learning models to personalize text-messages to encourage physical activity. The apps are designed for English & Spanish speaking individuals diagnosed with depression and diabetes, being treated at the ZSFGH.

Rankin, Kate

October 18, 2019 By Karen

Kate Rankin, PhD

Building Strategic Clinical Informatics Tools to Bridge Precision Medicine Research and Patient Care

Dr. Rankin investigates the underpinnings of human socioemotional behavior in aging and neurodegenerative disease with quantitative brain imaging, and develops tools for harmonizing cross-disciplinary data and analytic processes to facilitate scientific collaboration and clinical care.

Phillips, Kathryn

October 18, 2019 By Karen

Kathryn Phillips, PhD

Examining Health Services and Health Economics, focusing on new technologies to improve healthcare

Dr. Phillips focuses on the value of new technologies and how to effectively and efficiently implement them into health care. Her core specialty is precision medicine. Her work spans multiple disciplines, including basic, clinical & social sciences

Glymour, Maria

October 18, 2019 By Karen

Maria Glymour, ScD, MS

Causal Inference, Artificial Intelligence and Health Research

Dr. Glymour is exploring approaches of causal inference methods for research on health inequalities, stroke, and Alzheimer’s disease and how Artificial Intelligence can accelerate health research.

Murray, Sara

October 18, 2019 By Karen

Sara Murray, MD

Using EHR data for quality and value improvements

Dr. Murray is leading the Advanced Analytics & Innovation team, she is involved in large analytic projects using EHR data to inform quality and value improvement efforts at the medical center. She is interested in predictive analytics and has done research in EHR phenotyping.

Sanders, Stephan

October 18, 2019 By Karen

Stephan Sanders, PhD

Using genomics and bioinformatics to understand the etiology of developmental disorders

Sanders Lab aims to identify the etiology of developmental disorders through the discovery of genetic risk factors. They aim to continue progress, leverage findings to build a complete understanding of ASD, & extend this approach to other human disorders, including congenital malformations.

Hong, Julian

October 17, 2019 By Karen

Julian Hong, MD, MS

Developing and implementing computational tools in oncology to improve patient care

Dr. Hong’s research program focuses on combining clinical domain knowledge with data science to generate insights from real world data, develop actionable computational tools, and evaluate the benefit of these advances in personalized cancer care.

Li, Jingjing

October 17, 2019 By Karen

Jingjing Li, PhD

From Big Data to Big Mind: Building Data-Driven Frameworks to Solve Complex Diseases

The main theme of our research is large-scale analysis of disease genomes by integrating multi-omics data, evolutionary insights, electronic health records, as well as digitized clinical traits from imaging and wearable sensor readouts. The ultimate goal is to build data-driven frameworks to detect diseases before symptoms emerge and to achieve precision health management.

Brain Maps Allow Individualized Predictions of FTD Progression

Brain Maps Allow Individualized Predictions of FTD Progression
Source: UCSF
October 14, 2019

Seeley and colleagues used maps of brain connections to predict how brain atrophy would spread in individual patients with frontotemporal dementia.

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UCSF Launches Artificial Intelligence Center to Advance Medical Imaging

UCSF Launches Artificial Intelligence Center to Advance Medical Imaging
Source: UCSF
October 11, 2019

Majumdar will run the Center for Intelligent Imaging’s operations to accelerate the application of artificial intelligence (AI) technology to radiology.

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FDA approves Artificial Intelligence Algorithm That Reads Chest X-Rays

FDA approves Artificial Intelligence Algorithm That Reads Chest X-Rays
Source: UCSF
September 12, 2019

Callcut led the product development of the new AI screening tool, known as Critical Care Suite, which is being licensed by UCSF Innovation Venture to GE Healthcare.

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Genetic Test Found a Life-Saving Therapy for an Infant’s Rare Cancer

Genetic Test Found a Life-Saving Therapy for an Infant's Rare Cancer
Source: UCSF
September 11, 2019

Alejandro Sweet-Cordero, explains how the UCSF500 test can identify inherited predispositions to cancer and help patients design prevention and surveillance strategies.

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Mobile Devices and Health

Mobile Devices and Health
Source: New England Journal of Medicine
September 5, 2019

UCSF, Cornell Tech, Sage Bionetworks, Open mHealth and The Commons Project are collaborating to integrate EHR data to Android smartphones.

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Alzheimer’s Disease Destroys Neurons that Keep Us Awake

Alzheimer’s Disease Destroys Neurons that Keep Us Awake
Source: UCSF
August 12, 2019

Study suggests tau tangles, not amyloid plaques, drive daytime napping that precedes dementia.

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AI For All — Data-Driven Summer Program Energizes a New Generation

AI For All — Data-Driven Summer Program Energizes a New Generation
Source: UCSF Precision Medicine
August 14, 2019

BCHSI faculty Marina Sirota led the first cohort of the AI4All program, focused on promoting greater diversity and inclusion in the field of AI in biomedicine.

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Tison, Geoff

August 7, 2019 By Karen

Geoff Tison, MD, MPH

Applying machine learning and deep-learning techniques to large-scale electronic health data

Dr. Tison applies machine learning and deep-learning techniques to large-scale electronic health data from heterogeneous sources in order to achieve the goal of personalized cardiovascular prognosis and disease prevention.

Rosner, Benjamin

August 5, 2019 By Karen

Benjamin Rosner, MD, PhD

Understand use of CLIIR to improve quality and value of healthcare

Audit-log data captures moment to moment clinical care processes within EHR. It makes these labor-intensive approaches obsolete, providing more comprehensive data faster with more accuracy. Taking this audit-log data and combining it with clinical data enables us to research the impact of provider workflows, behaviors and interactions with the EHR on patient outcomes.

University of California announces data science collaboration with Janssen

UC & Janssen Collaboration
Source: University of California
June 28, 2019

New fellowship program from UCSF’s BCHSI, UC Berkeley’s BIDS, and Janssen Research & Development to recruit data scientists for innovative, high-impact, data-driven healthcare research

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Ramani, Vijay

June 27, 2019 By Karen

Vijay Ramani, PhD

Novel molecular technologies to study gene regulation

Ramani Lab invents molecular tools to study biology, e.g. devising ways to molecularly tag nucleic acids and proteins with unique genomic or proteomic identifiers, then using these to quantify biological phenomena at the level of single cells and single molecules, using high-throughput sequencing and cutting-edge mass spectrometric techniques.

Huang, Franklin

June 24, 2019 By Karen

Franklin Huang, MD, PhD

Understanding how to use digital tools to improve quality and value of healthcare

Dr. Huang studies biological processes relating to cancer disparities with a focus in prostate cancer. His lab uses cancer genomics including single-cell approaches to understand mechanisms that drive lethal, aggressive disease. A major focus is to identify and uncover roles for cancer genes and identify new cancer vulnerabilities.

Whooley, Mary

June 24, 2019 By Karen

Mary Whooley, MD

Learning Health Systems & Cardiovascular Outcomes Research

Dr. Whooley’s work focuses on applying the methods of health services research (including data science, implementation science, and program evaluation) to accelerate the adoption of evidence-based practices within the context of a national learning healthcare system. One of her specific interest areas is in the domain of cardiovascular health outcomes.

Larson, Peder

June 24, 2019 By Karen

Peder Larson, PhD

Developing new MRI scanning and reconstruction technology for improved clinical outcomes

Dr. Larson’s research program focuses on developments aimed at several applications: Metabolic imaging methods using hyperpolarized carbon-13 MRI; Semi-solid tissue MRI, for imaging of tendons, cortical bone, myelin, and lung tissue; and PET/MRI systems that combine the exceptional soft-tissue contrast of MRI with the functional contrast of PET.

Pirrachio, Romain

June 24, 2019 By Karen

Romain Pirrachio, MD, PhD

Applied biostatistical research, machine Learning and predictive analytics in critical care

Dr. Pirracchio focuses on three clinical research areas including evaluation and optimization of daily cares in the intensive care unit. He is also broadly interested in problems of causal inference and prediction, particularly developing novel methodologies for addressing scientific questions using complex observational data subject to sampling biases.

New Collaboration To Advance Patient Safety In The Digital Era

New Collaboration To Advance Patient Safety In The Digital Era
Source: CISION PR Newswire
May 7, 2019

Julia Adler-Milstein will lead the new partnership between UCSF and The Doctor’s Company to make substantive advances in patient safety and digital health.

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Seo, Youngho

November 9, 2018 By Karen

Youngho Seo, PhD

Using quantitative SPECT/CT, PET/CT, and PET/MR molecular imaging tools for a broad range of research areas

Dr. Seo applies his expertise in radionuclide and x-ray imaging physics and instrumentation to develop quantitative imaging techniques for everything from small animal research to analysis of clinical research data.

Pedoia, Valentina

November 9, 2018 By Karen

Valentina Pedoia, PhD

Using machine learning to extract features from MRI to study degenerative joint disease

Dr. Pedoia develops analytics to model the complex interactions between morphological, biochemical and biomechanical aspects of the knee joint as a whole; deep learning convolutional neural network for musculoskeletal tissue segmentation and for the extraction of silent features from quantitative relaxation maps for a comprehensive study of the biochemical articular cartilage composition; with ultimate goal of developing a completely data-driven model that is able to extract imaging features and use them to identify risk factors and predict outcomes for Osteoarthritis.

Goldstein, Ted

November 9, 2018 By Karen

Ted Goldstien, PhD

Applying Bioinformatics to Precision Medicine

Dr. Goldstien uses the tools of big data, statistics and machine learning to answer questions related to Precision Medicine such as: How can we learn from the inventory of genomic test and knowledge in the EMR about patient outcomes and the data associated with individual patients to better direct their care? How can we better use repeatable animal models to translate knowledge to human patients? How can we integrate existing knowledge and high throughput data? Can we use genomic data to bring new therapies to bear?

Zaitlen, Noah

March 12, 2018 By Karen

Noah Zaitlen, PhD

Understanding genetic and environmental underpinnings of common disease

The Zaitlen lab develops statistical and computational tools to discover the genetic basis of complex phenotypes, with particular interest in human disease, variation in drug/treatment response, and disease outcomes. Current projects primarily focus on incorporating environmental context into medical genetics.

Van t’Veer, Laura

March 10, 2018 By Karen

Laura Van t’Veer, PhD

Characterizing biomolecular signatures for precision cancer treatments

Dr. van ‘t Veer’s research focuses on personalized medicine, to advance patient management based on knowledge of the genetic make-up of the tumor as well as the genetic make-up of the patient. This allows clinicians to optimally assign systemic therapy for those patients in need of such treatment, and to ensure the selection of the therapy that is most effective.

Hess, Christopher

March 10, 2018 By Karen

Christopher Hess, MD, PhD

Developing and translating biomedical imaging to diagnose and treat neurological disease

Dr. Hess’s research interests lie in the development and translational application of magnetic resonance imaging techniques for diagnosis and treatment monitoring in neurologic disease. His scientific background is in MRI acquisition, reconstruction and image analysis, focusing on diffusion and high-field MRI. His primary clinical interests are in neurovascular disease, dementia, brain development, and epilepsy.

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