Spring 2018 Courses


Biomedical Informatics Project Course (3 credits)

This course provides an opportunity for students to apply concepts that they learned in BIOINF 2011 to carry out a one-term research project. They will be asked to identify, plan, develop, carry out, and report on such a project. This hands-on course will encourage students to think more deeply and concretely about the concepts and methods presented in BIOINF 2011 and in doing so to develop a better understanding of that material. This course will also serve as an early, mentored introduction to performing biomedical informatics research.

Instructor:  Gregory F. Cooper, M.D.

Term:  Spring

Days/Times:  Tuesdays/Thursdays from 1:30 p.m. to 3:00 p.m.

Location:  407A BAUM, 5607 Baum Blvd.

Prerequisites: BIOINF 2011 – Introduction to Biomedical Informatics.

Recitations:  None


Biomedical Informatics Colloquium (Lecture Series) (This is not a formal course.)

This course meets once each week for one hour.  The current research of Biomedical Informatics faculty and senior fellows will be presented.

Instructor:  Various speakers

Term:  Fall and Spring

Days/Times:  Fridays, 11:00 a.m. to 12:00 noon

Location:  407A BAUM, 5607 Baum Blvd.



Biomedical Informatics Journal Club (ISSP 2083) (1 credit)

Biomedical informatics is a broad field encompassing many different research domains. What all of the domains have in common is the need to review and publish scientific papers and to give talks that present research to different audiences. The aim of this journal club is to expose students to recent research in various topics of biomedical informatics and to teach students how to critique a research article, present research from a research study; and critique a verbal presentation of research.

Instructor:  Xinghua Lu, M.D., Ph.D. and Ervin Sejdic, Ph.D.

Term:  Spring

Days/Times:  Fridays, 10:00 a.m. to 11:00 a.m.

Location:  536B BAUM, 5607 Baum Blvd.



Statistical Foundations of Biomedical Informatics (3 credits)

This is an introductory probability and statistics course intended primarily for biomedical informatics students. The first part of the course covers probability, including basic probability, random variables, univariate and multivariate distributions, transformations, expectation, numerical integration, and approximations. The second part of the course covers statistics, including study design, classical parametric inference, hypothesis testing, Bayesian inference, non-parametric methods, classification, ANOVA, and regression. We will use R for statistical computing and applications. Examples and applications will focus on biomedical informatics and related discipline.

Instructor:  Roger Day, Sc.D.

Term:  Spring

Days/Times:  Tuesdays/Thursdays, 3:00 p.m. to 4:30 p.m.

Location407A BAUM, 5607 Baum Blvd.

Expected class size:  10-15



Probabilistic Methods in Artificial Intelligence (3 credits)

This course is designed for students who do not necessarily have a background in computer science and want to learn and apply methods in artificial intelligence to problems in biomedicine. The course will introduce and provide the foundations artificial intelligence methods in search, probabilistic knowledge representation and reasoning, and machine learning with applications to biomedical informatics. Prerequisites for this course include introductory mathematics and programming.

Instructor:  Shyam Visweswaran, MD, PhD, Xia Jiang, Ph.D. and Madhavi Ganapathiraju, Ph.D.

Term:  Spring

Days/Times:  Monday/Wednesday from 12:30-2:00 p.m.

Location:  407A BAUM, 5607 Baum Blvd.

Prerequisites:  Introductory Mathematics and Programming

Expected class size:  10-15



Special Topic: Architecture of Interoperability (3 credits)

This course is designed to provide an overview of the tools, organizations, and current efforts to create healthcare interoperability.  Subjects will include: FHIR (and SMART on FHIR), Various modeling paradigms, Organizations involved with interoperability, and Computer architecture.

Instructor:  Steve Hasley, M.D.

Term:  Spring

Days/Times:  Monday from 9:00-12:00 p.m.

Location:  407A BAUM, 5607 Baum Blvd.

Prerequisites:  BIOINF 2011

Expected class size:  10-15


BIOINF 2480 (1-6 credits)

Masters Thesis/Project Research


BIOINF 2990 (1-14 credits)  

Masters Independent Study


BIOINF 2993 (1-9 credits)

Masters Directed Study


BIOINF 3990 (1-14 credits)

Doctoral Independent Study


BIOINF 3995 (1-9 credits)

Doctoral Directed Study


BIOINF 3998 (3 credits)

Doctoral Teaching Practicum


BIOINF 3999 (1-9 credits)

Doctoral Dissertation Research


NOTE:  Students registering for Full-time Dissertation Study must register under the School of Medicine’s Course Number:   FTDS 0000 (0 credits)