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Events for January 20, 2017

  • CS Colloquium and CAIS Seminar: Eva K Lee (GATECH) - System interoperability & Machine Learning: Multi-site Evidence-based Best Practice Discovery

    Fri, Jan 20, 2017 @ 11:00 AM - 11:50 AM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Eva K Lee, Georgia Institute of Technology

    Talk Title: System interoperability & Machine Learning: Multi-site Evidence-based Best Practice Discovery

    Series: Center for AI in Society (CAIS) Seminar Series

    Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.

    This study establishes interoperability among electronic medical records from 737 healthcare sites and performs machine learning for best practice discovery. A mapping algorithm is designed to disambiguate free text entries and to provide a unique and unified way to link content to structured medical concepts despite the extreme variations that can occur during clinical diagnosis documentation. Redundancy is reduced through concept mapping. A SNOMED-CT graph database is created to allow for rapid data access and queries. These integrated data can be accessed through a secured web-based portal. A classification model ((DAMIP) is then designed to uncover discriminatory characteristics that can predict the quality of treatment outcome. We demonstrate system usability by analyzing Type II diabetic patients. DAMIP establishes a classification rule on a training set which results in greater than 80% blind predictive accuracy on an independent set of patients. By including features obtained from structured concept mapping, the predictive accuracy is improved to over 88%. The results facilitate evidence-based treatment and optimization of site performance through best practice dissemination and knowledge transfer. This project receives the 2016 NSF Health Organization Transformation award.

    Biography: Dr. Lee is a Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology, and Director of the Center for Operations Research in Medicine and HealthCare, a center established through funds from the National Science Foundation and the Whitaker Foundation. The center focuses on biomedicine, public health, and defense, advancing domains from basic science to translational medical research; intelligent, quality, and cost-effective delivery; and medical preparedness and protection of critical infrastructures. She is a Distinguished Scholar in Health Systems, Health System Institute at Georgia Tech and Emory University. She is also the Co-Director of the Center for Health Organization Transformation, an NSF Industry/University Cooperative Research Center. Lee partners with hospital leaders to develop novel transformational strategies in delivery, quality, safety, operations efficiency, information management, change management and organizational learning. Lee's research focuses on mathematical programming, information technology, and computational algorithms for risk assessment, decision making, predictive analytics and knowledge discovery, and systems optimization. She has made major contributions in advances to medical care and procedures, emergency response and medical preparedness, healthcare operations, and business operations transformation.
    Dr. Lee serves on the National Preparedness and Response Science Board. She is the principle investigator of an online interoperable information exchange and decision support system for mass dispensing, emergency response, and casualty mitigation. The system integrates disease spread modeling with response processes and human behavior; and offers efficiency and quality assurance in operations and logistics performance. It currently has over 9500+ public health site users. Lee has also performed field work within the U.S. on mass dispensing design and evaluation, and has worked with local emergency responders and affected populations after Hurricane Katrina, the Haiti earthquake, the Fukushima Japan radiological disaster, and Hurricane Sandy. Lee has received multiple analytics and practice excellence awards including INFORMS Franz Edelman award, Daniel H Wagner prize for novel cancer therapeutics, bioterrorism emergency response dispensing for mass casualty mitigation, optimizing and transforming clinical workflow and patient care, vaccine immunity prediction, and reducing hospital acquired conditions. Dr. Lee is an INFORMS Fellow. She has received seven patents on innovative medical systems and devices. A brief glimpse of Dr. Lee's healthcare work can be found in the following link: http://www2.isye.gatech.edu/~evakylee/Eva_Lee_Intl_Innovation_139_Research_Media_HR.pdf

    Host: Milind Tambe

    Location: Seeley G. Mudd Building (SGM) - 101

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

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  • W.V.T. Rusch Engineering Honors Program Colloquium

    Fri, Jan 20, 2017 @ 01:00 PM - 01:50 PM

    USC Viterbi School of Engineering, Viterbi School of Engineering Student Affairs

    University Calendar


    Join us for a presentation by Dr. Emilio Ferrara, Research Professor of Computational Social Sciences at Information Sciences Institute, titled "The Rise of Social Bots."

    Location: Henry Salvatori Computer Science Center (SAL) - 101

    Audiences: Everyone Is Invited

    Contact: Ramon Borunda/Academic Services

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  • BME Special Seminar

    BME Special Seminar

    Fri, Jan 20, 2017 @ 02:30 PM - 03:30 PM

    Alfred E. Mann Department of Biomedical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dominique Duncan, Assistant Professor of Neurology, Keck School of Medicine, LONI

    Talk Title: Predicting Epileptogenesis after Traumatic Brain Injury and Using Virtual Reality to Correct Segmentation Errors in MRI

    Abstract: The first part of my talk focuses on identifying biomarkers that can predict epileptogenesis after traumatic brain injury (TBI). This project, The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx), is a multi-site, international collaboration including a parallel study of humans and rats, collecting MRI, EEG, and blood samples.

    Because the development of epilepsy following TBI is a multifactorial process and
    crosses multiple modalities, identifying biomarkers to quantify the condition has proved difficult. Without a full understanding of the underlying biological effects, there are currently no cures for epilepsy. This study hopes to address both issues, calling upon data generated and collected at sites spread worldwide among different laboratories, clinical sites, in different formats, and across multicenter preclinical trials. Before these data can even be analyzed, a central platform is needed to standardize these data and provide tools for searching, viewing, annotating, and analyzing them. We are building a centralized data archive for EEG that will link to the Laboratory of Neuro Imaging (LONI) Image Data Archive (IDA) for MRI data and allow the broader epilepsy research community to access this shared data in addition to analytic tools to identify and validate biomarkers of epileptogenesis in images and electrophysiology as well as in molecular, serological, and tissue studies.

    The second part of this talk focuses on crowdsourcing manual validation of algorithmically-segmented brain volumes using virtual reality. LONI has the largest collection/repository of neuroanatomical MRI scans in the world. One of the lab's workflow processes involves algorithmic segmentation of the scans into labeled anatomical regions using FreeSurfer software. Since this automation cannot yet achieve perfect accuracy, there is a team of students who are trained to fix these errors manually, which is a tedious, time-consuming process. We are working on transforming the way this is accomplished using VR technology (HTC Vive) to deal with the volumes directly in 3D space, which aims to be both more intuitive and efficient. The goal is to crowdsource this task to make the process even more efficient.


    Biography: http://loni.usc.edu/about_loni/people/indiv_detail.php?people_id=568

    Host: Biomedical Engineering Department

    Location: 146

    Audiences: Everyone Is Invited

    Contact: Mischalgrace Diasanta

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  • NL Seminar-HOW I LEARNED TO STOP WORRYING AND LOVE EVALUATIONS (AND KEEP WORRYING)

    Fri, Jan 20, 2017 @ 03:00 PM - 04:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Jon May, USC/ISI

    Talk Title: HOW I LEARNED TO STOP WORRYING AND LOVE EVALUATIONS (AND KEEP WORRYING)

    Series: Natural Language Seminar

    Abstract: Bake-offs, shared tasks, evaluations: these are names for short, high-stress periods in many CS researchers' lives where their algorithms and models are exposed to unseen data, often with reputations and funding on the line. Evaluations are sometimes perceived to be the bane of much of our work lives. We grouse about metrics, procedures, glitches, and all the time "wasted" chasing scores, rather than doing Real Science (TM). In this talk I will argue that despite valid criticisms of the approach, coordinated evaluation is a net benefit to NLP research and has led to accomplishments that might not have otherwise arisen. This argument will frame a more in-depth discussion of several pieces of recent evaluation-grounded work: rapid generation of translation and information extraction for low-resource surprise languages (DARPA LORELEI) and organization of SemEval shared tasks in semantic parsing and generation.




    Biography: Jonathan May is a Research Assistant Professor at the University of Southern California's Information Sciences Institute (USC/ISI). Previously, he was a research scientist at SDL Research (formerly Language Weaver) and a scientist at Raytheon BBN Technologies. He received a Ph.D. in Computer Science from the University of Southern California in 2010 and a BSE and MSE in Computer Science Engineering and Computer and Information Science, respectively, from the University of Pennsylvania in 2001. Jon's research interests include automata theory, natural language processing, machine translation, and machine learning.

    Host: Marjan Ghazvininejad and Kevin Knight

    More Info: http://nlg.isi.edu/nl-seminar/

    Location: Information Science Institute (ISI) - 6th Flr -CR#689 (ISI/Marina Del Rey)

    Audiences: Everyone Is Invited

    Contact: Peter Zamar

    Event Link: http://nlg.isi.edu/nl-seminar/

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