Spring 2020 Courses

 

BIOMEDICAL INFORMATICS (BIOINF) COURSES

SPRING TERM 2020 (subject to change)

 

 

BIOINF 2032

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.

 

BIOINF 2118

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:  Doug Landsittel, Ph.D.

Term:  Spring

Days/Times:  Tuesdays and Thursdays, 12:00 p.m. to 1:25 p.m.

Location:  407A BAUM, 5607 Baum Blvd.

Expected class size:  10-15

 

BIOINF 2071

Foundations of Biomedical Informatics 2 (3 credits) 

This course serves as an introduction to core methods and topics in biomedical informatics using the context of the Learning Health System (LHS). A LHS combines data and information managements, discovery, and application of discoveries to clinical and population health. Discussion of the challenges associated with the construction of a LHS will be used to contextualize and motivate content to be covered in the course (challenges and analysis and interpretation to create knowledge). 

Instructor:  Shyam Visweswaran, M.D., Ph.D.

Term:  Spring

Days/Times:  Mondays/Wednesdays 9:30 a.m. to 10:55 a.m.

Location:  407A BAUM, 5607 Baum Blvd.

Prerequisites:  CS 1501 Algorithm Implementation and CS 2710 Foundations of Artificial Intelligence

Expected class size: 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

 

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.

 

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

^