RUMI PARSE RISE Optimizing Stroke Treatment CDSC

RUMI

Many of us go online to get information about our medical conditions. But do you really understand the data in your medical record? The Retrieving Understandable Medical Information (RUMI) project aims to provide tailored, context-sensitive information to patients.

PARSE

With the increasing amount of data in the electronic health record, new methods are required to help expedite a healthcare provider's understanding of a patient's medical history. The PARSE project explores the use of topic models for summarizing large, unstructured data collections to support PCPs.

RISE

Are you an undergraduate interested in biomedical informatics? The MII Research in Informatics Summer Experience (MII RISE) is an opportunity for undergraduates to work with our faculty to gain experience in research and biomedical informatics.

Optimizing Stroke Treatment

Annually, it is estimated that more than 795,000 Americans experience a stroke. The severity of neurological damage due to an acute stroke is mitigated by the early restoration of blood flow to the affected area. In this project, new probabilistic modeling methods are being developed to optimally select treatments.

CDSC

The Center for Domain-Specific Computing (CDSC) is an NSF-InTrans award, focusing on next-generation hardware and software acceleration of algorithms in the biomedical sciences. CDSC is a collaboration between UCLA, Rice University, Oregon Health Sciences University, and Intel Research.


Research News


Paper published in Frontiers in Neuroinformatics
13 February 2017

The journal Frontiers in Neuroinformatics has published "Computer-Aided Experiment Planning toward Causal Discovery in Neuroscience," by MII student Nicholas J. Matiasz. Co-authors of this article include MII student Justin Wood, MII faculty member William Hsu, and collaborators Wei Wang and Alcino J. Silva.

Paper accepted to Computers in Biology and Medicine
09 January 2017

A paper by MII student Shiwen Shen titled "A Bayesian model for estimating multi-state disease progression" was accepted for publication in the journal Computers in Biology and Medicine.

Finalist best student paper in ICPR2016
21 December 2016

MII stu­dent Johnny Ho's paper, tit­led "A Tem­po­ral Deep Lear­ning Approach for MR Per­fusion Para­me­ter Esti­ma­tion in Stro­ke," was the fina­list in best IBM track5 stu­dent paper award.

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