Mar 29, 2024  
2017-2018 Graduate Catalog 
    
2017-2018 Graduate Catalog [ARCHIVED CATALOG]

Biomedical Data Science and Informatics, PhD


 

Program Description


Biomedical data science and informatics is an interdisciplinary field that combines ideas from computer science and quantitative disciplines-statistics, data science, decision science-to solve challenging problems in biology, medicine and public health.

Clemson University and the Medical University of South Carolina offer a joint PhD degree in Biomedical Data Science and Informatics. This unique collaboration combines Clemson’s strengths in computing, engineering, and public health with MUSC’s expertise in biomedical sciences to produce the next generation of data scientists, prepared to manage and analyze big data sources in order to improve health in the state and the nation. This program is unique to South Carolina and very few programs nationally focus on data science applied to the health and biomedical fields. 

The nation’s transition to new healthcare delivery models and the exponential growth in biomedical data translate to a need for professionals with expertise in data science focused in biomedical research who can leverage big data to improve health in the state and the nation. Graduates possess marketable skills for informatics careers in biology, medicine, or public health focused on the development of prescriptive analytics from large data sources and are prepared to lead research programs in academic, healthcare, public health, and industry. These specially trained scientists are critical to on-going efforts to improve health outcomes in South Carolina and the nation. Specialized tracks include precision medicine, population health, and clinical and translational informatics.

Students have a designated “home institution” at which they are typically physically located. However, all students in this program take graduate classes from both institutions. Students are not required to travel between campuses to take courses, as courses are available to students both on-campus and via synchronous remote connection. Courses are offered on the Clemson main campus, MUSC main campus, the University Center of Greenville, and the Zucker Family Graduate Education Center (on CURI campus, North Charleston).

For more information, please visit https://www.cs.clemson.edu/bdsi/

Admission

The annual deadline for applications is January 15. Individuals are encouraged to complete their application several weeks prior to deadline. A joint admissions committee reviews all applications and makes recommendations to the deans of the Clemson Graduate School and MUSC College of graduate Studies. The deans make final admissions decisions. Students typically begin their study in the fall semester.

Applicants identify a preference for a home institution when applying for admission to this joint program. The faculty joint selection committee considers the applicant’s preference and other considerations (e.g. number of openings, alignment of student’s research interests, funding) and makes the final home institution decisions.

This interdisciplinary program is designed for full-time students with undergraduate or graduate backgrounds in computer science, math, engineering, or biomedical sciences who wish to make a contribution to biomedical sciences or individual and public health. Recent graduates with advanced degrees (i.e., either masters or professional) or individuals with a bachelors and work experience are ideal candidates.

Admission Requirements

  • Bachelor’s degree in biomedical/health sciences, computing, mathematics, statistics, engineering, or related discipline
  • Submission of scores from the general GRE (may be waived for those who hold a US graduate or professional degree in a related area from an accredited program)
  • One year of calculus; one year of college biology
  • Computer programming coursework (e.g. at least one advanced programming course) or substantial experience in industry

Recommended Compentencies and Coursework

  • Competency in a second related area of the above list (biomedical/health sciences, computing, mathematics, statistics, engineering or related discipline), as demonstrated by completion of a major, minor or certificate
  • Relevant research or work experience
  • Coursework in multivariate calculus, linear algebra, probability and statistics, and biostatistics
  • One year of computer science coursework that focuses on the fundamentals of computer science and software engineering principles, including abstraction, modularity, and object-oriented programming 

Program Requirements


A PhD in Biomedical Data Science and Informatics requires 65-68 hours of coursework. Each student works with the graduate coordinator, academic advisor, and dissertation committee to construct a program of study that conforms to the requirements outlined below and takes into account both the student’s prior preparation and intended research area. In cases where a student enters the program with prior coursework in a required area, the graduate coordinator may approve a substitution. In cases where a student lacks prerequisites for a required course, the student will be asked to complete both the prerequisite coursework and the required course. Because the curriculum is tailored to each student, the time needed to complete the degree varies, but in general, it is expected that students can complete the degree in five years or less.

Research

This doctoral program is a research degree. Students pursue one of three track specialty areas, which include precision medicine, population health, and clinical and translational informatics. All students have the opportunity to work directly with one or more program faculty member on research related to data science and informatics. Doctoral students are immersed in the research environment and actively engage in authoring research proposals, conducting research, writing abstracts and manuscripts, and presenting research findings. 

Coursework


Students complete courses in each of the five areas below:

Area I: Biomedical Informatics Foundations and Applications (15-16 Credits)


Research Foundations (3 Credits)

Select one of the following:

  • Applied Statistical and Research Methods 3 Credits (MUSC course)
  • Applied Research 3 Credits (MUSC course)
Biomedical Informatics Foundations (6 Credits)

  • Introduction to Biomedical Informatics 3 Credits (MUSC course)
  • Biomedical Data Standards and Ontology 3 Credits (MUSC course)
Track Specific Core Course (3 Credits)

Select one of the following:

  • Precision Medicine Informatics 3 Credits (MUSC course)
  • Population Health Informatics 3 Credits (MUSC course)
  • Clinical and Translational Informatics 3 Credits (MUSC course)
Elective (Minimum 3 Credits)

Select one or two of the following:

  • Statistical Bioinformatics 3 Credits (MUSC course)
  • Panomics 3 Credits (MUSC course)
  • Consumer and Quantified Self 2 Credits (MUSC course)
  • Health Enterprise Analytics 2 Credits (MUSC course)

Area II: Computing, Mathematics, Statistics and Engineering (18 Credits)


Mathematical and Computing Foundations (3 Credits)

Select one of the following:

  • Mathematical Methods in Biomedical Imaging 3 Credits (MUSC course)
Data Science (9 Credits) Select 3 credits from Machine Learning/Data Science and 6 additional credits from two other different categories below.

Machine Learning/Data Science

Select one of the following:

  • Machine Learning 3 Credits (MUSC course)
Biostatistics

  • Introduction to Clinical Biostatistics (Biostatistics I) 3 Credits (MUSC course)
  • Biostatistical Methods II 3 Credits (MUSC course)
Data Mining

  • Bayesian Biostatistics 3 Credits (MUSC course)
Visualization and Exploratory Data Analysis

Image Processing

  • Signal and Image Processing 3 Credits (MUSC course)
Geospatial Analysis

  • GIS and Mapping for Public Health 3 Credits (MUSC course)
Natural Language Processing

  • Natural Language Processing 3 Credits (MUSC course)

Area III: Population Health, Health Systems and Policy (5-6 Credits)


Select two of the following:

  • Ethical, Legal and Regulatory Issues in Health Informatics 3 Credits (MUSC course)
  • Foundations of Epidemiology I 3 Credits (MUSC course)
  • Foundations of Epidemiology II 3 Credits (MUSC course)
  • Health Law and Risk Management 3 Credits (MUSC course)
  • Health Policy 3 Credits (MUSC course)
  • Quality Management of Health Care Services 3 Credits (MUSC course)

Area IV: Biological/Medical Domain (3-4 Credits)


Select one of the following:

  • Foundations of Biomedical Sciences I 4 Credits (MUSC course)
  • Foundations of Biomedical Sciences II 4 Credits (MUSC course)​

Area V: Lab Rotations, Seminars and Doctoral Research (24+ credits)


Lab Rotations

Students engage in lab rotations during the first two semesters. A maximum of 4 credits of lab rotation hours may be counted toward the degree, though students may choose to engage in additional lab rotation hours for experience.

Seminars

Students are required to attend a minimum of two seminars each semester on a credit or non-credit basis. All students must attend the Biomedical Data Science and Informatics seminar each semester; and select at least one additional seminar series related to their area of research. A maximum of 4 credits of seminars may be counted toward the degree, though students may choose to attend as many seminars as desired.

Doctoral Research

Once a topic has been selected, students register for doctoral research credits. A minimum of 18 credits is required for the degree, and a maximum of 18 hours may be counted towards the degree, though students many enroll in additional credits as needed, particularly to reflect the efforts of the student and the advisor while engaged in dissertation research.

 

Additional Requirements for Completion of Degree


  • Formation of a dissertation committee
  • Qualifying exam
  • Dissertation proposal
  • Defense of research
  • Dissertation