RUMI PARSE RISE Optimizing Stroke Treatment CDSC


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.


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.


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.


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

MII student wins RSNA Trainee Research Prize
16 September 2016

MII stu­dent Kart­hik Sarma has won a 2016 RSNA Trai­nee Research Prize for his pos­ter tit­led "An Inves­ti­ga­tio­nal Patch-­ba­sed Con­vo­lu­tio­nal Neu­ral Network Model for the Detec­tion of Cli­nically Sig­ni­ficant Pros­tate Cancer using Mul­ti­pa­ra­met­ric MRI."

3 students to present at RSNA 2016
26 July 2016

Three MII stu­dents, Johnny Ho, Edgar Rios, and Kart­hik Sar­ma, were accep­ted to pre­sent at the 2016 Radio­lo­gical Society of North Ame­rica annual mee­ting in November.

Paper accepted to Artificial Intelligence in Medicine
25 July 2016

A paper by MII student Panayiotis Petousis titled "Prediction of lung cancer incidence on the low-dose computed tomography arm of the National Lung Screening Trial: A dynamic Bayesian network" was accepted for publication in Artificial Intelligence in Medicine.

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