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You are here: Home / Archives for Uncategorized

Newly released updates to the Information Commons Environment

May 6, 2021 By Angela

The development team supporting our UCSF Information Commons Environment has been busy building and improving data assets, analysis tools, compute environments, and, of course, providing support and data science connections […]

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.

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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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.

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.

Atul Butte Inducted Into American Institute for Medical and Biological Engineering

Source: UCSF Precision Medicine
March 25, 2019

BCHSI’s Director has been inducted into the College of Fellows of the AIMBE in recognition of his contributions to creating a precision medicine roadmap with open access data

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Automatic Hip Fracture Identification and Functional Classification with Deep Learning

September 25, 2018 By Angela

Justin D. Krogue MD, Kaiyang Cheng, Kevin Hwang MD, Eugene Ozhinsky PhD, Sharmila Majumdar PhD, Valentina Pedoia PhD Overview: Hip fractures represent an important cause of morbidity, with more than […]

Adler-Milstein, Julia

November 16, 2017 By Karen

Julia Adler-Milstein, PhD

Examining the use of IT in healthcare delivery

Dr. Adler-Milstein’s research assesses the progress of health IT adoption; the impact of such adoption on healthcare costs and quality; and the relationships between market, organizational, and team structure and health IT use. A core focus of her work is on health information exchange and interoperability.

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