Clemson - MUSC AI Hub
The Clemson-MUSC AI Hub, a joint effort by Clemson University and the Medical University of South Carolina, focuses on AI in biomedical science and healthcare research.
This alliance, funded by both institutions, promotes AI technologies in clinical research, computational biology, and healthcare informatics. Our mission includes creating an industry portal for collaboration, developing ethical AI solutions in healthcare, catalyzing AI research for funding, and building strong partnerships to lead in biomedical AI research.
What are the applications of AI in healthcare and how do they vary?
Artificial Intelligence
This feature enables machines to learn tasks instead of just executing programmed computations, marking a significant advancement in technology.
Machine Learning
This AI approach involves developing algorithms to analyze and predict outcomes based on input data, such as personalized news feeds or traffic forecasts.
Neural Networks
Modeled after the brain, these algorithms process signals through interconnected nodes (artificial neurons), effectively recognizing and predicting patterns in neural signals crucial for brain functions.
Deep Learning
This form of machine learning, using layered computations, creates deep neural networks capable of learning from complex, unstructured data, evident in applications like voice-controlled assistants and self-driving cars.
How does AI contribute to enhancing healthcare and biomedical research?
Radiology
AI aids in interpreting imaging results, potentially detecting subtle changes that may elude human observation.
Imaging
AI is utilized in assessing post-surgery outcomes like facial reconstructions, enhancing precision in medical procedures.
Telehealth
Wearable tech, integrated with AI, constantly monitors patients, detecting physiological changes and providing early alerts for conditions like asthma attacks.
Clinical Decision Support Systems
AI is extensively used to develop systems assisting clinicians with treatment decisions by leveraging health data and case knowledge.
AI Consulting
The AI Program services include machine learning and deep learning for a variety of data types including EHR data, clinical text, images or other data types. The consultations are ideal for applying AI-based methods to current or future research.
Membership
Free to join, sign up to receive announcements on upcoming events, seminars, continuing education and more!
Our Mission
Our mission is to expand and promote the use, understanding and research of artificial intelligence and related technologies in the biomedical/population health domain across Clemson and MUSC. We will pursue the following initiatives to accomplish this mission.
- Provide a portal for industry, philanthropy and investors from the community and region to support and collaborate within this expanding area of innovation.
- Develop and support AI technologies to improve population health, empower providers, enhance value and reduce cost in a manner that keeps ethics, diversity and inclusion at the forefront.
- Catalyze AI research in pursuit of funding and leadership in the field both regionally and nationally.
- Create productive relationships that produce high quality research and solidify Clemson and MUSC as leaders in biomedical and population health AI related research.
AI Hub Leadership
G. Hamilton Baker, M.D.
Associate Professor of Pediatrics (Cardiology)
Undergraduate:
University of Michigan
Medical School:
Albany Medical College
Residency:
Medical University of South Carolina
Fellowship:
Medical University of South Carolina
Specialty:
General Cardiology
Jihad Obeid, M.D.
Assistant Vice President for Research – AI Strategy & Research Intelligence
Professor, College of Medicine – Public Health Sciences
Professor, College of Medicine – Public Health Sciences
mail
jobeid@musc.edu
call
(843) 792-0272
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Dr. Obeid is a Professor and SmartState Endowed Chair in Biomedical Informatics in the Department of Public Health Sciences at the Medical University of South Carolina (MUSC). Dr. Obeid is a pediatrician who was formally trained in Medical Informatics at the Division of Health Sciences and Technology, a joint Harvard-MIT fellowship program.
He served as the Associate Director of the Biomedical Informatics Center (BMIC) for over a decade where he led the development of several academic and operational research informatics initiatives including the electronic health records (EHR) Research Data Warehouse (RDW), REDCap, and many others. Since his arrival at MUSC, he has served as principal investigator, co-investigator, and informatics leader on numerous federally funded projects. At the national level, he led several working groups related to translational research informatics. Dr. Obeid is the founder and director of two courses in Biomedical Informatics (MCR-746: Informatics and Data Management for Clinical Research and BDSI-712: Translational Informatics).
His research interests include artificial intelligence (AI), specifically, deep learning and large language models applications using EHR data for e-phenotyping and predictive modeling with focus on clinical text mining. Other research interests include natural language processing, electronic consents, secondary use of EHR data/data warehousing, and biomedical ontologies.
Dr. Obeid is the co-founder of the AI Hub at MUSC. He serves as the director of the Cancer Integrated Data Enabled Resource (CIDER), which integrates a variety of multimodal data, and provides several services to researchers including, consultations, feasibility queries, brokered access to integrated data, and AI and NLP research services.
Hudson Smith, Ph.D.
Assistant Professor of Math & Statistical Sciences at Clemson University
Chris McMahan, Ph.D.
Associate Professor of Math & Statistical Sciences at Clemson University
Student AI Hub
The Student AI hub is a group of interprofessional graduate students at MUSC who aims to expand and promote the use, understanding and research of artificial intelligence and related technologies at the university. We do this by providing a portal for experts from the community to collaborate and educate members of the group, create the environment to promote mentor relationships that produce high quality research, grant funding, and innovative technology, and support students in the creation of innovative ideas.
Overall, we hope to promote innovative thinking while keeping ethics, diversity and inclusion at the forefront of these efforts in order to solidify MUSC as a lead in the field of artificial intelligence technology.
Introductory Educational Resources
AI/ML Education Series
Visit this link to register for future course offerings and to replay previously recorded courses.
This education series was held by the following industry sponsors: NVIDIA, NetApp, and Mark III Systems.
Reading Materials & Free Textbooks
Deep Learning Book - HTML webpage with PDFs of MIT's free machine learning textbook