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X-WR-CALNAME:USC Big Data Health Science Center
X-ORIGINAL-URL:https://bigdata.sc.edu
X-WR-CALDESC:Events for USC Big Data Health Science Center
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BEGIN:VTIMEZONE
TZID:UTC
BEGIN:STANDARD
TZOFFSETFROM:+0000
TZOFFSETTO:+0000
TZNAME:UTC
DTSTART:20180101T000000
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END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=UTC:20200424T110000
DTEND;TZID=UTC:20200424T120000
DTSTAMP:20260421T212435
CREATED:20200421T204341Z
LAST-MODIFIED:20200512T142136Z
UID:882-1587726000-1587729600@bigdata.sc.edu
SUMMARY:BDHSC Live Lecture: Big Data in the Time of COVID-19
DESCRIPTION:BDHSC invites UofSC Faculty/Staff and Students to a live lecture. \n\n\nWhen: Apr 24\, 2020 11:00 AM Eastern Time (US and Canada)\nTopic: Live Lecture: Data Science in the Time of COVID-19 \nRegister in advance for this webinar:\nhttps://zoom.us/webinar/register/WN_xntSAcMVTW6KwxM1xt1M8w\nAfter registering\, you will receive a confirmation email containing information about joining the webinar. \n \n  \n  \n  \n  \n\n\n  \n 
URL:https://bigdata.sc.edu/event/bdhsc-live-lecture-big-data-in-the-time-of-covid-19/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20200226T110000
DTEND;TZID=UTC:20200226T123000
DTSTAMP:20260421T212435
CREATED:20200211T163737Z
LAST-MODIFIED:20200212T134404Z
UID:501-1582714800-1582720200@bigdata.sc.edu
SUMMARY:“Bayesian Regression for Group Testing Data”
DESCRIPTION:Abstract:\nGroup testing involves pooling individual specimens (e.g.\, blood\, urine\, swabs\, etc.) and testing the pools for the presence of a disease. When individual covariate information is available (e.g.\, age\, gender\, number of sexual partners\, etc.)\, a common goal is to relate an individual’s true disease status to the covariates in a regression model. Estimating this relationship is a nonstandard problem in group testing because true individual statuses are not observed and all testing responses (on pools and on individuals) are subject to misclassification arising from assay error. Previous regression methods for group testing data can be inefficient because they are restricted to using only initial pool responses and/or they make potentially unrealistic assumptions regarding the assay accuracy probabilities. To overcome these limitations\, we propose a general Bayesian regression framework for modeling group testing data. The novelty of our approach is that it can be easily implemented with data from any group testing protocol. Furthermore\, our approach will simultaneously estimate assay accuracy probabilities (along with the covariate effects) and can even be applied in screening situations where multiple assays are used. We apply our methods to group testing data collected in Iowa as part of statewide screening efforts for chlamydia\, and we make user-friendly R code available to practitioners. \nAbout the speaker:\nDr. Tebbs is Professor and Chair in the Department of Statistics\, USC\, an Associate Editor at Statistics in Medicine and a member of the Biostatistical Methods and Research Design Study Section of the NIH. Dr. Tebbs’ primary research interests are in the development of statistical methods for categorical data\, especially aggregated or group tested data and their application in infectious disease screening\, as well as in general biostatistical methods and problems involving ordering or shape restrictions. His research program is funded by the NIH. \nRegister at https://www.eventbrite.com/e/uofsc-bdhscs-monthly-seminars-tickets-93359339297
URL:https://bigdata.sc.edu/event/bayesian-regression-for-group-testing-data/
LOCATION:Room 140\, Discovery I\, 915 Greene Street\, Columbia\, SC\, 29208\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20200209
DTEND;VALUE=DATE:20200212
DTSTAMP:20260421T212435
CREATED:20191209T043643Z
LAST-MODIFIED:20191209T043732Z
UID:324-1581206400-1581465599@bigdata.sc.edu
SUMMARY:UofSC National Big Data Health Science Conference
DESCRIPTION:UofSC National Big Data Health Science Conference \nThe University of South Carolina’s National Big Data Health Science Conference is a signature annual event of the UofSC Big Data Health Science Center (BDHSC). The theme for the 2020 Conference: Unlocking the Power of Big Data in Health – Partnerships among Industry\, Government\, and Academia. https://www.sc-bdhs-conference.org/ \nRegister at https://www.sc-bdhs-conference.org/registration-information/
URL:https://bigdata.sc.edu/event/uofsc-national-big-data-health-science-conference/
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20200207
DTEND;VALUE=DATE:20200210
DTSTAMP:20260421T212435
CREATED:20191209T043602Z
LAST-MODIFIED:20191209T043809Z
UID:322-1581033600-1581292799@bigdata.sc.edu
SUMMARY:UofSC National Big Data Health Science Conference\, Case Competition 2020
DESCRIPTION:UofSC National Big Data Health Science Conference\, Case Competition 2020 \nThe Big Data Health Science Case Competition will be held between February 7th-9th 2020 before the University of South Carolina’s National Big Data Health Science Conference. The Big Data Case Competition is intended to provide enthusiastic teams of graduate and senior undergraduate students with the opportunity to apply their knowledge to the analysis of big datasets in healthcare.\nhttps://www.sc-bdhs-conference.org/case-competition/ \nRegister at https://www.sc-bdhs-conference.org/registration-information/
URL:https://bigdata.sc.edu/event/uofsc-national-big-data-health-science-conference-case-competition-2020/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20200129T110000
DTEND;TZID=UTC:20200129T123000
DTSTAMP:20260421T212435
CREATED:20200125T162322Z
LAST-MODIFIED:20200125T162322Z
UID:455-1580295600-1580301000@bigdata.sc.edu
SUMMARY:“Leveraging Social Media Technology to Improve Health and Emotional Well-being”
DESCRIPTION:“Leveraging Social Media Technology to Improve Health and Emotional Well-being” \nAbstract:\nDr. Cavazos will present on systematic ways to explore social media posts about mental illness and substance misuse behaviors. Her research has implications for the delivery of online\, accessible\, and timely social media outreach that could facilitate new and more rapid responses in mental health promotion\, prevention\, and harm reduction initiatives. \nAbout the speaker:\nDr. Patricia A. Cavazos is an Associate Professor in the Department of Psychiatry at Washington University School of Medicine in St. Louis. She is a clinically trained licensed psychologist who has been involved in biomedical research for over 15 years. Funded by the National Institutes of Health (NIH)\, her research program leverages social media technology to help those struggling with substance use disorders and mental illness. \nRegister at https://www.eventbrite.com/e/uofsc-bdhscs-monthly-seminars-tickets-88540030615 \n \n 
URL:https://bigdata.sc.edu/event/leveraging-social-media-technology-to-improve-health-and-emotional-well-being/
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20191030
DTEND;VALUE=DATE:20191031
DTSTAMP:20260421T212435
CREATED:20191209T043217Z
LAST-MODIFIED:20200608T195825Z
UID:316-1572393600-1572479999@bigdata.sc.edu
SUMMARY:“Integrating Multi-Modal Biobehavioral Data to Treat Substance Use Disorders” Seminar
DESCRIPTION:“Integrating Multi-Modal Biobehavioral Data to Treat Substance Use Disorders” Seminar\, Dr. Brett Froeliger\, Medical University of South Carolina \nAbstract:\nThe role of neural circuitry in motivation\, reward and drug use will be discussed; along with associations between inhibitory control and relapse vulnerability. These topics will be discussed in the context of ongoing research on the potential value of 3 bio-behavioral treatments for substance use disorders. \nAbout the speaker:\nBrett Froeliger\, PhD is an Associate Professor in the Department of Neuroscience\, Neuroscience Graduate Program Director and Director of the Translational Research of Addiction and Integrative Neuroscience laboratory at the Medical University of South Carolina. He also holds an Adjunct Faculty position at Duke University Medical Center in the Department of Psychiatry and Behavioral Sciences and at the University of South Carolina in the Department of Pharmacy. His program of research has been continuously funded by NIH / NIDA since 2012 and is organized around using fMRI to evaluate the potential benefit of novel pharmacotherapies\, behavioral interventions and\, most recently\, neural stimulation for treating substance use disorder pathophysiology. \nRegister at https://www.eventbrite.com/e/uofsc-bdhscs-monthly-seminars-tickets-76972594101
URL:https://bigdata.sc.edu/event/integrating-multi-modal-biobehavioral-data-to-treat-substance-use-disorders-seminar/
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20190925
DTEND;VALUE=DATE:20190926
DTSTAMP:20260421T212435
CREATED:20191209T043121Z
LAST-MODIFIED:20200608T195916Z
UID:314-1569369600-1569455999@bigdata.sc.edu
SUMMARY:“Utilizing Big Data for Drug Discovery (Repurposing) to Improve Patient and Disease Outcomes” Seminar
DESCRIPTION:“Utilizing Big Data for Drug Discovery (Repurposing) to Improve Patient and Disease Outcomes” Seminar\, Dr. Scott Sutton\, UofSC \nAbstract:\nDrug repurposing holds the potential to bring existing medications with known safety profiles to new patient populations to accelerate drug development and lower treatment costs. Numerous examples exist for the identification of new indications for existing compounds and identified from unanticipated findings or focused efforts to the mechanism of action of a specific drug. In recent years\, the need for new approaches to drug research and development\, combined with the advent of big data repositories and associated analytical methods\, has generated interest in developing systematic approaches to drug repurposing. In this presentation\, we describe our approach to systematic repurposing and discuss the need for strategic collaborations to increase the likelihood of success in bringing existing molecules to new indications. The research examples utilized as big data examples include influenza\, diabetes\, Alzheimer’s\, and Colorectal cancer. \nAbout the speaker:\nhttps://www.sc.edu/study/colleges_schools/pharmacy/faculty-staff/sutton_scott.php \nRegister at https://www.eventbrite.com/e/uofsc-bdhscs-monthly-seminars-tickets-70941739653
URL:https://bigdata.sc.edu/event/utilizing-big-data-for-drug-discovery-repurposing-to-improve-patient-and-disease-outcomes-seminar/
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20190828
DTEND;VALUE=DATE:20190829
DTSTAMP:20260421T212435
CREATED:20191209T042914Z
LAST-MODIFIED:20200608T195700Z
UID:312-1566950400-1567036799@bigdata.sc.edu
SUMMARY:“Neuroimaging Data Collection in NIH StrokeNet Clinical Trials” Seminar
DESCRIPTION:“Neuroimaging Data Collection in NIH StrokeNet Clinical Trials” Seminar\, Dr. Wenle Zhao\, Medical University of South Carolina \nAbstract:\nEstablished in 2014\, the NIH StrokeNet is designed to conduct large multicenter clinical trials for stroke acute treatment\, recovery\, and prevention. The Data Coordination Unit at the Medical University of South Carolina is the National Data Management Center for the StrokeNet\, managing 8 concurrent stroke trials today. Most of these trials involve neuroimaging for eligibility and efficacy outcome assessments. This talk will present measures implemented for fast file uploading\, PHI data cleaning\, and neuroimaging central read and scoring\, and wishes for automated neuroimaging processing. \nAbout the speaker:\nDr. Zhao is a research professor in the Department of Public Health Sciences at the Medical University of South Carolina. He obtained his BS and MS in Mechanical Engineering at Zhejiang University\, China\, and his PhD in Biostatistics at MUSC. His research interest covers subject randomization algorithm in clinical trials and integrated information system for clinical trial data and operation management. \nRegister at https://www.eventbrite.com/e/the-uofsc-bdhscs-monthly-seminars-tickets-65242083829
URL:https://bigdata.sc.edu/event/neuroimaging-data-collection-in-nih-strokenet-clinical-trials-seminar/
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