USC Big Data Health Science Center

Canceled: An Overview of the South Carolina Alzheimer’s Disease Registry
2022-08-26 11:00 - 12:00 UTC | Room 140, Discovery I, 915 Greene Street, Columbia, SC, 29208, United States
An Overview of the South Carolina Alzheimer’s Disease Registry by Dr. Maggi Miller (UofSC).
Register for in-person attendance (boxed lunch provided) at https://forms.gle/enuNSyA7owBGWvnx7.
Register for virtual attendance at https://us02web.zoom.us/webinar/register/WN_NTzdK2VXTQeihlx23Wvm1g.

NIMH Division of AIDS Research Funding Opportunities and Priorities in Data Science
2022-09-28 11:00 - 12:00 | Koger Center for the Arts, Gallery Room, 1051 Greene St, Columbia, SC, 29201, United States
NIMH Division of AIDS Research Funding Opportunities and Priorities in Data Science by Dr. Lori Scott-Sheldon (Chief of Data Science and Emerging Methodologies in HIV at the National Institute of Mental Health).
Register at https://forms.gle/RbVP3yd44BNwf5uL9
Boxed lunch provided on first come first served basis.
No virtual option available but check our website in the weeks following for a recording.

Big Data Health Science Center Annual Retreat 2022
2022-09-30 09:00 - 13:00 | Campus Room, Capstone Hall, 902 Barnwell St, Columbia, SC, 29208, United States
ePlease see the below for information about the upcoming BDHSC retreat and networking luncheon (9/30). This event is intended for BDHSC affiliates and stakeholders to gather and discuss extramurally funded research, opportunities for collaboration, and challenges in data acquisition. Students must seek permission prior to registering. BDHSC faculty affiliates and core members are encouraged to attend.
Register (in-person only) at BDHSC Annual Retreat Registration (google.com).

BDHSC Pilot Project Showcase
2022-10-28 11:00 - 12:00 | Room 140, Discovery I, 915 Greene Street, Columbia, SC, 29208, United States
Join us as we hear about the projects of four 2021 Big Data Health Science Center Pilot Project Recipients!
Friday, October 28 from 11-12pm
In-person: Discovery 1, Room 140 and virtual option available
Registration required. Register at in-person: https://docs.google.com/forms/d/e/1FAIpQLScNdjmGrrp3u2bfyZtsGMvvV7VAJ7T7Y0FXT2qm0jSOvo2w9w/viewform?usp=sf_link
Virtual: https://us02web.zoom.us/webinar/register/WN_znlpwqA5SKuS7277fz2lrg or by scanning the QR code below.
Lunch provided.
Dezhi Wu, Ph.D., College of Engineering and Computing
Exploring Sentiment and Communication Exchange Patterns of Substance Use Disorder (SUD) Associated with Pregnant Women on Twitter Before and During COVID-19 Pandemic
Substance use among pregnant women is a significant public health concern. Recent studies have shown an alarming increase in substance use; however, it is still unknown how the COVID-19 pandemic has impacted vulnerable pregnant women. We applied NLP, text mining and machine learning techniques to extract just-in-time substance use (SU) data among pregnant women on Twitter, and then explored their communication patterns, risky health perceptions, sentiment, and maternal and fetal health outcomes. Our study findings are informative to perinatal healthcare practice and related public health policy changes.
Peiyin Hung, Ph.D., Arnold School of Public Health
Rural and Racial Disparities in Maternal Telehealth Health Care Access during the COVID-19 Pandemic.
Ensuring equitable telehealth uptake in prenatal care is critical for the optimal outcomes of newly developed prenatal care guidelines. This study aims to quantify the trends of prenatal care via telehealth before and during the COVID-19 pandemic, and assess the variations by maternal race, ethnicity, and residence. We used a statewide Medicaid claims data for Medicaid-insured women in South Carolina to assess prenatal telehealth uptake before and during the COVID-19 pandemic. Using an interrupted time series approach, we found that prenatal care visits via telehealth uptake increased substantially at the beginning of the COVID-19 pandemic, decreased within a few months, but remained more prevalent than the pre-pandemic rates. This study highlights the disproportionate telehealth access among rural women and women from racial minority groups who have historically faced barriers to accessing prenatal care.
Greg Trevors, Ph.D., College of Education
Identifying Optimal Vaccine Promotion Messages for Vulnerable Subgroups from Large-Scale Gamified Interventions
The long-term goal of this project is to inform the design of subsequent digital health promotion interventions that will dynamically personalize to participants based on empirical insights gained from machine learning analyses on our large-scale digital intervention data. To accomplish these long-term goals, the immediate objectives in this proposal are (1) identify distinct vaccine hesitancy subgroups from our prior intervention participants; and (2) identify optimal content that is associated with an increase likelihood of healthy behavioral intentions and attitudes, including vaccine intent and confidence, for each VH subgroup.
Chen Liang, Ph.D., Arnold School of Public Health
Deep Phenotyping individuals with PASC using a Graph representational model of S3C
Studies found 47-87% of patients with persistent symptoms and multi-system organ dysfunction after the acute phase of COVID-19, denoted as Post-Acute Sequela of SARS-CoV-2 infection (PASC). Leveraging a biomedical informatics and data science approach, we will design an innovative Graph representational model on top of a multi-center clinical dataset [South Carolina COVID-19 Cohort (S3C), NIH/NIAID R01A127203-4S1]. Using this Graph model, we will develop and pilot test a new semi-supervised machine-learning deep phenotyping algorithm to identify individuals with PASC and characterize their electronic phenotypes. This study will result in a clinically plausible, interpretable, generalizable, and high-throughput deep phenotyping algorithm application for identifying possible PASC cases at COVID-19 recovery clinics, supporting patient referral, outreach, and therapeutics development.

Alzheimer's Disease Registry Seminar
2022-11-16 10:30 - 11:30 | Room 140, Discovery I, 915 Greene Street, Columbia, SC, 29208, United States
An Overview of the South Carolina Alzheimer’s Disease Registry by Dr. Maggi Miller (USC).
Register at https://forms.gle/LVZDeiz1SmtNHc19A.

Learning Individualized Treatment Rules with Many Treatments
2022-12-07 11:00 - 12:00 | Virtual
Please join us on December 7 for a virtual seminar “Learning Individualized Treatment Rules with Many Treatments” by Dr. Yufeng Liu, the University of North Carolina at Chapel Hill. This seminar is hosted by our Electronic Health Records Core.
Registration required. Please REGISTER HERE

Deadline for Abstracts Submission - 2023 Annual Big Data Health Science Conference
2022-12-12
The Big Data Health Science Center is seeking research and program-based abstracts for oral and poster presentations responsive to its 4th annual conference theme, “Unlocking the Power of Big Data in Health: Translating Data Science into Program Development and Implementation”. This conference will be held in-person at the Pastides Alumni Center in Columbia, SC on February 10-11,2023. Accepted abstracts will be published in conference proceedings Research and program-based abstracts in the areas of infectious diseases, AI for Sensing and Diagnosis, EHR, social media data, genomics analysis, geospatial research, GIS, infrastructural and capacity development, professional development, community/industry engagement, academic training, and methodological advances are desired.
Learn more at https://www.sc-bdhs-conference.org/.

BDHSC Pilot Project Showcase Part 2
2023-01-25 13:00 - 14:00 | Room 140, Discovery I, 915 Greene Street, Columbia, SC, 29208, United States
Please join us for a Big Data seminar showcasing 4 of our 2021 pilot project recipients. Speakers will discuss their research questions, data, methods, and future directions. This event is free and boxed lunch will be provided on a first come first served basis. Register at https://forms.gle/RoryZogDVET3FCRF9.

National Big Data Health Science Student Case Competition 2023
2023-02-03 - 2023-02-05 | Virtual

National Big Data Health Science Conference 2023
2023-02-10 - 2023-02-11 | Pastides Alumni Center, Columbia, SC, 900 Senate St, Columbia, SC, 29201, United States

Deadline for NIH-funded T35 Research Training Program Applications
2023-02-15

Deadline for 2023 Health GIS Scholars Program
2023-03-01

An Overview of the Federal Statistical Research Data Centers
2023-03-22 12:00 - 13:00 | Zoom Webinar

Deadline for 2023 Pilot Project Proposals
2023-04-14
University of South Carolina Big Data Health Science Center (BDHSC) is seeking proposals for the conduct and uptake of pilot research projects focusing on the Big Data analytics in addressing critical issues related to health behavior, healthcare, and population health.
The purpose of this RFP is to invite pilot project applications on the utilization of Big Data analytics in health-related research. The primary goals of this pilot project program will be to promote interdisciplinary collaboration in Big Data health science research and support meritorious applications that can leverage existing data to address critical issues related to health behavior, clinical care, healthcare delivery, and population health. Interdisciplinary research that involves linking and integrating data sets from multiple sources are particularly encouraged. Existing data may include, but are not limited to electronic health records data, social media data, geospatial data, genomic data, or artificial intelligence for sensing and diagnosis. To get more information, please check out the full 2023 Pilot Project RFP here.
For questions regarding this RFP and proposal submission, please contact Ms. Miranda Nixon at mc95@mailbox.sc.edu; 803-777-5027.

NSF ACCESS HPC Monthly Workshop: Machine Learning and Big Data
2023-05-23 11:00 - 2023-05-24 17:30
Research Computing and the USC Big Health Data Science Center will jointly co-host an in-person NSF ACCESS HPC Monthly Workshop on “Machine Learning and Big Data” sponsored by ACCESS and presented by the Pittsburgh Supercomputing Center. The workshop will be held on May 23-24, 2023, from 11AM-5PM on May 23 and 11AM-5:30PM on May 24.
This workshop will focus on topics including big data analytics and machine learning with Spark, and deep learning using Tensorflow. This will be an IN-PERSON event hosted by various satellite sites, there WILL NOT be a direct to desktop option for this event. Registration is on a first come first served basis. Interested applicants must first have an ACCESS ID. If you do not have an ACCESS ID, please visit this page to create one:
ACCESS USER REGISTRATION
Once you have an ACCESS ID, please complete the following registration page by Sunday, May 21 at Noon Eastern time:
Eventbrite Reservation
Classroom location and further details will be provided once your registration has been processed.

Summer Workshops in Bioinformatics and Data Analytics
2023-06-12 10:00 - 2023-07-14 16:00
Please use the below form to register for the workshops.
https://forms.gle/2q98LD1BKtVr9b7z9

Utilizing Big Spatiotemporal Data to Understand COVID and its Impact
2023-08-30 10:30 - 11:30 | Room 140, Discovery I, 915 Greene Street, Columbia, SC, 29208, United States
Utilizing Big Spatiotemporal Data to Understand COVID and its Impacts by Dr. Chaowei Phil Yang

Event Time: Wednesday August 30, 2023 @10:30-11:30am
Event Address: Discovery Building, Rm 140 (915 Greene St, Columbia, SC 29201)
Please register here.Spatiotemporal

Big Data Health Science Center Annual Retreat 2023
2023-09-29 09:00 - 13:00 | Campus Room, Capstone Hall, 902 Barnwell St, Columbia, SC, 29208, United States
Please join us for the 2023 BDHSC Annual Retreat. See below for full details. Please help us to get an accurate head count for food by registering here.

This retreat is geared towards faculty. Post docs and doctoral candidates welcome.

The Rhino Federated Computing Platform Unlocks the World's Data Silos for Collaborative Research
2023-10-25 11:30 - 12:30 | Virtual
Please join us for our October 25th (11:30-12:30) Big Data seminar featuring Dr. Malhar Patel, Director of Clinical Engagement at Rhino Health.
Register for this free virtual event at https://us02web.zoom.us/webinar/register/WN_yYq0S83RT0693cpOXjkiig

Place Matters: Utility of Geospatial Data in Health Research
2023-11-29 11:00 - 12:00 | Virtual
Registration required. Register here. https://us02web.zoom.us/webinar/register/WN_899MmYukTsSvvV5RYkRDkg.

The increasing focus on health equity research will require projects that examine and address the geographic contexts where we live, work, and play. Such contexts are important drivers of health inequities given that the characteristics of neighborhoods and other spaces have been driven by historic and current structural inequities. This seminar will provide an orientation to spatial framing and methods, including traditional and emerging spatial methodologies such as global positioning systems (GPS) and location aware technologies.
Dr. Katherine Theall is a Professor at Tulane University’s School of Public Health and Tropical Medicine, Senior Director of the Tulane Violence Prevention Institute and Director of the Mary Amelia Center for Women’s Health Equity Research. As a social and spatial epidemiologist, her research focuses on reducing health inequities by understanding and altering neighborhood environments and social policies in underserved populations locally, nationally, and internationally. She has been PI or co-PI of more than 25 federally- and privately-supported research and training awards and has a highly interdisciplinary background, with educational and practical experience in social/spatial epidemiology and community health and prevention sciences. Her work involves close collaboration with both state and city governments as well as international partners, where she has been involved in research, programming, and translational efforts to improve health equity and well-being.

A Bayesian Machine Learning Approach for Estimating Heterogeneous Survivor Causal Effects: Applications To a Critical Care Trial
2023-12-07 10:00 - 11:00 | Koger Center for the Arts, Gallery Room, 1051 Greene St, Columbia, SC, 29201, United States
Registration is required. Please register here.

National Big Data Health Science Student Case Competition 2024
2024-01-26 - 2024-01-28 | Virtual

National Big Data Health Science Conference 2024
2024-02-02 - 2024-02-03 | Columbia Metropolitan Convention Center, 1101 Lincoln St, Columbia, SC, 29201, United States
Funding for this conference was made possible (in part) by R13LM014347 from the National Library of Medicine. The views expressed in written conference materials or publications and by speakers and moderators do not necessarily reflect the official policies of the Department of Health and Human Services; nor does mention by trade names, commercial practices, or organizations imply endorsement by the U.S. Government.

Deadline for Big Data Analytics Emerging Scholar Training Program for URM Undergrads in SC
2024-03-01
The USC Big Data Health Science Center is now accepting applications for the BDHSC’s newly funded training program, Big Data Analytics Emerging Scholar Training Program for URM Undergrads in South Carolina (1R25AI172761-01). Please click for full details about the program, including eligibility, application process, FAQ, etc. The application deadline is March 1, 2024.

Deadline for Big Data Health Science Fellow Program
2024-03-14
Supported by NIAID (R25AI164581-03), the USC Big Data Health Science Center (BDHSC) has been implementing a Big Data Health Science Fellow (“Big Data Fellow”) program since 2021. The program will recruit around 4 USC junior faculty per year and provide them with salary support (25%) to participate in the training program. Please click to see the call for applications to the 2024-2025 Big Data Health Science Fellow program. Details about program requirements, eligibility, and deadlines can be found in the Request for Applications. Apply by March 14, 2024.

Geospatial Modeling for Disease Vector Surveillance in Brazil and Beyond
2024-04-11 15:00 - 16:00 | Discovery Room 259, 915 Greene Street, Columbia, SC, 29201, United States
Please join the Big Data Health Science Center for its 37th seminar featuring Dr. Gabriel Z. Laporta from Centro Universitário FMABC.

Geospatial Modeling for Disease Vector Surveillance in Brazil and Beyond
Thursday, April 11 | 3:00-4:00pm
Discovery Room 259
To receive a link for virtual attendance, register at https://us02web.zoom.us/webinar/register/WN_SWwAHafFQgqMbqBb7VDOpg.

NSF ACCESS HPC Monthly Workshop on “Machine Learning and Big Data”
2024-07-31 - 2024-08-01 | Innovation Center Building Room 1400, 550 Assembly Street, Columbia, SC, 29201, United States
The USC Research Computing, Division of Information Technology, and Big Data Health Science Center will host a remote site for the NSF ACCESS NSF ACCESS HPC Monthly Workshop on “Machine Learning and Big Data” presented by the Pittsburgh Supercomputing Center. The workshop will be held on July 31 and August 1, 2024, from 11 a.m. to 5 p.m. in Room 1400 of the Innovation Center Building, 550 Assembly Street, Columbia, SC 29201. This will be an in-person event hosted by various satellite sites; there WILL NOT be a direct-to-desktop option for this event.
This workshop will focus on topics including big data analytics, machine learning using Spark, and deep learning using Tensorflow.
The deadline to register for this event is July 26, 2024. Interested applicants must first set up an access ID. For instructions on how to set up your ACCESS ID and register for this workshop, please visit the “HPC Monthly Workshop: Machine Learning and Big Data” webpage at https://www.psc.edu/resources/training/hpc-workshop-big-data-july-2024/.

Deadline to apply for Community Scholar (c-Scholar) Training Program
2024-08-23 08:00 - 17:00
Read more about the c-Scholar program at https://bigdata.sc.edu/r25-c-scholar-program/
The NIH Strategic Plan for Data Science suggests that a Big Data approach will uniquely advance our understanding of disease prevention, identification, control, and treatment in the coming decades and will be a key to reducing national and global health disparities. Despite rapidly increased efforts in the application of Big Data and advanced data analytics for health science research, the progress of translating Big Data research findings to effective public health and clinical practices for improved health outcomes has been slow due to many challenges. Such challenges include the limited participation of community members in Big Data health science research and a lack of effective communication between data science researchers and communities. As a multi-stakeholder effort, health data science crosses boundaries between research and practice, as well as between science and health policy. The involvement of and communication with members of local communities is critical to actualizing the benefits of data science research.
To address this critical need for community involvement in Big Data health science research, we offer data science training and mentored hands-on research experience to a group of community scholars through the R25 Community Scholar (“c-Scholar”) program. Guided by a citizen science model, the c-Scholar program provides structured support to four community scholars from various governmental and community organizations in South Carolina each year. Specifically, the R25 c-Scholar program (1) identifies and recruits community members interested in participating in Big Data infectious disease research and utilizing Big Data research findings to improve the health outcomes of their communities; (2) implements a multi-module training program that provides mentoring, curriculum-based training, and hands-on research experience to better equip c-Scholars with necessary knowledge, skills, and competence for Big Data infectious disease research; and (3) trains and supports c-Scholars to promote and utilize Big Data research in their communities by developing or improving their necessary professional skills (e.g., health communication, presentation of scientific findings to the public, community outreach and engagement).
Interested individuals should attach their resume or CV to an email expressing their interest in the program and their desire to promote and utilize Big Data infectious disease research in their community to Dr. Banky Olatosi (olatosi@mailbox.sc.edu) by close of business on August 23, 2024.
The R25 Executive Committee will evaluate all applications and contact finalists for additional documentation, including a letter from their employer or supervisor stating their approval and agreement for the applicant to participate in this one-year program.
Important Dates (subject to change)
Application deadline: August 23, 2024
Selection of finalists: September 2, 2024
Formal acceptance of offer and submission of follow up documentation: September 9, 2024
Program start: October 8, 2024

Big Data Health Science Center 2024 Retreat
2024-09-27 09:00 - 13:00
Please join us for the 2024 BDHSC Annual Retreat
Friday, September 27
9am-1pm (with a networking luncheon from 12-1pm)
Campus Room, Capstone Building, USC Columbia Campus

Connect with USC leadership and representatives from government agencies and community partners
Identify opportunities for collaboration with faculty engaged in Big Data research
Network via round table discussions and a networking luncheon

This retreat is intended for USC faculty. Postdocs and doctoral candidates must receive prior approval from BDHSC before registering. Email Miranda Nixon at mc95@mailbox.sc.edu with inquiries.
Registration required. Register today at https://forms.gle/h9X2h9grdL1UqhCz8

Vector-Borne Diseases in Colombia: Current Situation of Dengue Fever and Chagas Disease and the Potential use of Big Data in the Solution of these Problems
2024-10-09 10:00 - 11:00
Vector-Borne Diseases in Colombia: Current Situation of Dengue Fever and Chagas Disease and the Potential use of Big Data in the Solution of these Problems
Dr. Omar Cantillo-Barraza,
Institute of Biology, Biology and Infectious Disease Control Laboratory, University of Antioquia
October 9 | 10-11am
Discovery Building Rm 331 (915 Greene St)
This seminar will be conducted in a hybrid format, with in-person attendance encouraged. Online attendance via Teams
