AI/Machine Learning/Data Science

G. Hamilton Baker, M.D.

baker@musc.edu

The mission of the MUSC AI Hub is to expand and promote the use, understanding and research of artificial intelligence and related technologies at MUSC. The goal is to weave artificial intelligence into MUSC’s tripartite mission to optimize human health through patient care, research, and education. The AI Hub aims to create productive relationships that produce high quality research that solidifies MUSC as a leader in this field. This survey is designed to connect you to a research project in AI/Machine Learning/Data Science.

Click on this link to go to the survey.

 

Alexender Alekseyenko, Ph.D.

alekseye@musc.edu

We enable personalized healthcare by comprehensive understanding of host-microbiome interactions and integration of health data on individuals, communities and populations. We do this by developing interdisciplinary translatable methodologies for integration of microbiome data with patient information.

Students who have a potential interest in biomedical informatics, data science, machine learning or AI should contact Dr. Alekseyenko.

Please visit our web site for more information.

 

Arman Kilic, M.D.

welcbret@musc.edu

Arman Kilic, M.D., Director of the Harvey and Marcia Schiller Surgical Innovation Center, is an internationally recognized expert on AI / ML. He has more than 20 years of experience in risk modeling, advanced analytics, and using large multi-center data registries. Dr. Kilic serves on the Society of Thoracic Surgeons AI/ML Task Force, and has received funding from the National Institutes of Health and Thoracic Surgery Foundation for his work on AI in cardiac surgery. Clinically, Dr. Kilic serves MUSC Health as Surgical Director of Heart Transplant and Heart Failure and leads the Cardiogenic Shock Team. Research at the center primarily focuses on reporting surgical outcomes and developing AI models to augment clinical decisions.

 

Charles Terry, M.D.

terrych@musc.edu

I'm an assistant professor in the Department of Medicine, Division of Pulmonary and Critical Care looking for a student with expertise in computer science and bioinformatics to help me with a research project.

My interest is primarily in pragmatic observational clinical research in critical care. Presently, I'm designing a project to study how we can diagnose and better characterize Acute Respiratory Distress Syndrome from a diverse dataset of mechanically ventilated patients. This is a multidisciplinary project with collaborations from BMIC, College of Health Professions, and the pulmonary and critical care divisions.

I'm looking for a student ideally with a background in computer science and coding experience in python to collaborate with mentors in the BMIC department who are experts in natural language processing. This would be an excellent project with high visibility and publication potential in the fields of machine learning, NLP, and pulmonary/critical care.