Document text
Principal Investigator: Neset Hikmet
Organization: UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
Fiscal Year: 2024
Award: $131,713
Funding agency: National Institute of Allergy and Infectious Diseases
Abstract
Today, a critical mass of previously collected linked health care data is now available for
optimizing patient health outcomes. Information, insights, and intelligence existing in such health
care data can be unlocked efficiently using Big Data Science (BDS).As people age and live
longer, increased demand for care will be two-fold, one for those living with more comorbidities,
and second the emergent risks from new infectious diseases like COVID-19.The recent NIAID
strategic plan for COVID-19 highlights the urgent and important need for high-quality scientific
research to improve knowledge around disease transmission, surveillance, and its impact on
health outcomes, and to develop both biomedical and public health measures to mitigate illness
and death. The existence of several massive, and information rich big data streams in
healthcare (e.g., electronic health records [EHR], mobile technologies, wearable devices,
genomic data, geospatial data etc.) and the advances in information and computational
technologies (e.g., machine learning and artificial intelligence) now offer an excellent hands-on
training opportunity for applying innovative Big Data science (BDS) research to infectious
diseases such as HIV/AIDS and COVID-19. To cultivate a thriving and talented pipeline of next
generation scientists, it is essential to engage current students early and provide new and
innovative training opportunities to generate interest in the biomedical, social, and behavioral,
and clinical sciences. Therefore, we propose offering a 10-week Short-Term Summer Research
Training Program titled “Big Data Health Science Scholar Program for Infectious Diseases”
targeted towards predoctoral students in physical and/or quantitative sciences (departments of
biomedical engineering, integrated information technology, chemistry/biochemistry,
mathematics, statistics etc.) from across South Carolina (SC) and the United States (US).
Predoctoral students completing this training will engage in experiential learning through hands-
on research in infectious disease areas like HIV/AIDS, and COVID-19, both relevant to the
NIAID mission. Selected predoctoral students will be paired with Program Faculty mentors from
a pool of distinguished participating faculty for one-on-one mentoring. Trainees will be chosen
through a competitive process based on their proposed research plan and goals for the summer
experience. Specifically, we plan to recruit 8 predoctoral students from physical and quantitative
sciences across the US per year (a total of 40 over the entire funding period) to participate in
the 10-week summer intensive training program with the following objectives:
Objective 1: Create a summer big data science training pipeline for qualified predoctoral
students by exposing them to relevant courses/training for competency development in the
application of BDS to infectious disease research.
Objective 2: Engage trainees in hands-on research using HIV and COVID-19 data.
Objective 3: Provide trainees with rich research mentoring experience in BDS research and
professional development for at least one year (summer included). The proposed training
program will be implemented with support of the existing infrastructure of USC's Big Data Health
Center (BDHSC). The BDHSC, one of the USC's Excellence initiatives, promotes and supports
Big Data health science research at USC and across SC through capacity development,
academic training, professional development, community engagement, and methodological
advancement. BDHSC contains 5 content cores (EHR, geospatial, genomic, social media, and
bio-nanomaterial) and two supporting hubs (business/entrepreneurship and technology) with the
involvement of 43 faculty from 10 USC college/schools. Upon the completion of the proposed
training, each trainee is expected to: 1) complete 12 hours of academic training; 2) obtain
hands-on BDS experience working on NIAID-funded research databases; and 3) develop at
least one BDS manuscript on HIV or COVID-19 with their Program Faculty mentor. The training
program will foster the research environment to encourage diverse applicants, including those
from underrepresented groups, to pursue further Big Data health science research in HIV,
COVID-19 and other NIAID focus areas.
Terms: <AI system><AIDS Virus><AIDS/HIV><Academic Training><Acquired Immune Deficiency Syndrome Virus><Acquired Immunodeficiency Syndrome Virus><Active Learning><Age><Area><Artificial Intelligence><Behavioral Sciences><Big Data><BigData><Biochemistry><Biological Chemistry><Biomedical Engineering><Businesses><COVID-19><CV-19><Caring><Cessation of life><Chemistry><Clinical Sciences><Communicable Diseases><Competence><Computer Reasoning><Cooperative Learning><Coronavirus Infectious Disease 2019><Data><Data Bases><Databases><Death><Development><Electronic Health Record><Entrepreneurial Skill><Entrepreneurship><Environment><Experiential Learning><Faculty><Fostering><Funding><Genomics><Goals><HIV><HIV/AIDS><Health><Health Sciences><Healthcare><Hour><Human Immunodeficiency Viruses><Infectious Disease Pathway><Infectious Diseases><Infectious Diseases / Laboratory><Infectious Diseases Research><Infectious Disorder><Information Technology><Infrastructure><Intelligence><Knowledge><LAV-HTLV-III><Link><Lymphadenopathy-Associated Virus><Machine Intelligence><Machine Learning><Manuscripts><Math><Mathematics><Measures><Mentors><Methodology><Mission><NIAID><National Institute of Allergy and Infectious Disease><Outcome><Patients><Persons><Ph D student><Ph D. student><Ph. D. student><Ph.D student><Ph.D. student><PhD student><PhD. student><Process><Public Health><Qualifying><Research><Risk><Scholars Program><Schools><Science><Scientist><Social Sciences><South Carolina><Strategic Planning><Students><Talents><Technology><Training><Training Programs><Underrepresented Groups><Underrepresented Populations><United States><Virus-HIV><ages><big-data science><bio-engineered><bio-engineers><bioengineering><biological engineering><co-morbid><co-morbidity><college><collegiate><communicable disease transmission><community engagement><comorbidity><coronavirus disease 2019><coronavirus disease-19><coronavirus infectious disease-19><data base><data streams><developmental><disease transmission><doctoral student><electronic health care record><electronic health medical record><electronic health plan record><electronic health registry><electronic medical health record><engagement with communities><experience><faculty mentor><genomic data><genomic data-set><genomic dataset><hands on research><health care><health data><health science research><improved><infectious disease transmission><innovate><innovation><innovative><insight><interest><machine based learning><mobile computing><mobile platform><mobile technology><next generation><pre-doc><pre-doctoral><predoctoral><programs><recruit><social media><statistics><summer research><training opportunity><under representation of groups><under represented groups><under represented people><under represented populations><underrepresentation of groups><underrepresented people><wearable><wearable device><wearable electronics><wearable system><wearable technology><wearable tool><wearables>