Biostatistics and Medical Informatics course catalog
All 41 recorded UW–Madison courses in this department, including courses not offered this term. Open a course for prerequisites, historical grades and instructors.
BIOCHEM/BME/BMI/CBE/COMPSCI/GENETICS 915: Computation and Informatics in Biology and Medicine
1 credits
Participants and outside speakers will discuss current research in computation and informatics in biology and medicine. This seminar is required of all CIBM program trainees.
BIOCHEM/BMI/BMOLCHEM/MATH 609: Mathematical Methods for Systems Biology
Credits unavailable
Provides a rigorous foundation for mathematical modeling of biological systems. Mathematical techniques include dynamical systems and differential equations. Applications to biological pathways, including understanding of bistability within chemical reaction systems, are emphasized.
BMI 544: Introduction to Clinical and Healthcare Research II
Credits unavailable
Practical training and skills required in clinical and healthcare research; design, implementation, and conduct of clinical trials and health services research studies; protocol and informed consent development using protocol templates; regulatory requirements; human subjects research protections considerations; data and safety monitoring plans; data collection strategies and data management; strategies to recruit/retain diverse and equitable study participants; research study agreements; budget development and justification; federal, institutional, and sponsor-defined requirements; establishment of research infrastructures for participant safety and study success; preparation of investigator-INDs/IDEs; and investigator responsibilities.
BMI 573: Foundations of Data-driven Healthcare
Credits unavailable
Familiarize students with basic informatics principles and techniques to support clinical research and quality improvement studies from a perspective of data-driven approaches. Content includes information systems for study design; regulatory compliance; use of electronic health records data for research; data collection and acquisition; data security, storage, transfer, processing and analysis.
BMI 699: Independent Study
1–8 credits
Directed study to pursue knowledge beyond curriculum.
BMI 738: Ethics for Data Scientists
Credits unavailable
Designed to educate data scientists, particularly those who work with biomedical data, about ethical and regulatory issues that may arise in the course of their research and professional interactions.
BMI 773: Clinical Research Informatics
Credits unavailable
Course will familiarize students with basic informatics principles and techniques to support clinical research. Content includes information systems for protocol design; regulatory compliance; approaches for patient recruitment; efficient protocol management; data collection and acquisition; data security, storage, transfer, processing and analysis.
BMI 800: Becoming a Biomedical Data Scientist
1 credits
Learn how to conduct research as an interdisciplinary scientist at the interface of biomedical sciences and data science. Consider the diverse career trajectories available to an individual scientist. Gain an overview of problems in the field, approaches and practices in biomedical research, and different examples of approaches and paths taken from conceptualization to implementation of computational/statistical/data science tools to address specific biomedical research problems.
BMI 826: Special Topics in Biostatistics and Biomedical Informatics
Credits unavailable
Covers advanced topics in the areas of biostatistics and biomedical informatics. Includes reading and discussion of original literature and individual student projects.
BMI 881: Biomedical Data Science Scholarly Literature 1
2 credits
Critical evaluation of scholarly literature is a crucial skill for researchers. Develops that skill through focused reading and discussion of influential journal articles from the biomedical sciences, including biostatistics, biomedical informatics, and relevant areas of statistics and computer science.
BMI 882: Biomedical Data Science Scholarly Literature 2
Credits unavailable
Develops the ability to critically evaluate scholarly literature, a key skill for researchers. Focuses on reading and discussing a range of influential journal articles from the biomedical sciences, including topics in biostatistics, biomedical informatics, and relevant areas of statistics and computer science.
BMI 883: Biomedical Data Science Professional Skills 1
1 credits
A variety of skills that are important for a successful research career are often left to students to develop on their own. This course attempts to fill many of those gaps, including writing and reviewing papers, securing research funding, giving talks, presenting posters, making a personal website, job opportunities in universities and industry, and teaching.
BMI 884: Biomedical Data Science Professional Skills 2
1 credits
A variety of skills that are important for a successful research career are often left to students to develop on their own. This course attempts to fill many of those gaps, including writing and reviewing papers, securing research funding, giving talks, presenting posters, making a personal website, job opportunities in universities and industry, and teaching.
BMI 899: Pre-dissertator Research
1–12 credits
Pre-dissertator Research. Course is open to pre-dissertator students only.
BMI 990: Dissertator Research
1–3 credits
Dissertator Research. Course is open to dissertators only.
BMI/COMPSCI 567: Biomedical Image Analysis
Credits unavailable
Hands-on introduction to biological and medical image analysis techniques. Topics include medical imaging formats, segmentation, registration, image quantification, and classification.
BMI/COMPSCI 576: Introduction to Bioinformatics
3 credits
Algorithms for computational problems in molecular biology. Studies algorithms for problems such as: genome sequencing and mapping, pairwise and multiple sequence alignment, modeling sequence classes and features, phylogenetic tree construction, and gene-expression data analysis.
BMI/COMPSCI 767: Computational Methods for Medical Image Analysis
Credits unavailable
Review of advanced medical image analysis techniques. Covers advanced segmentation and registration methods. Describes the use and extension of statistical and machine learning methods for medical image analysis tasks.
BMI/COMPSCI 771: Learning Based Methods for Computer Vision
3 credits
Addresses the problems of representation and reasoning for large amounts of visual data, including images and videos, medical imaging data, and their associated tags or text descriptions. Introduces deep learning in the context of computer vision. Covers topics on visual recognition using deep models, such as image classification, object detection, human pose estimation, action recognition, 3D understanding, and medical image analysis. Emphasizes the design of vision and learning algorithms and models, as well as their practical implementations. Strongly recommended to have knowledge in computer vision or machine learning [such asCOMP SCI 540] or medical image analysis [such as B M I /COMP SCI/B M I 567].
BMI/COMPSCI 775: Computational Network Biology
3 credits
Introduces networks as a powerful representation in many real-world domains including biology and biomedicine. Encompasses theory and applications of networks, also referred to as graphs, to study complex systems such as living organisms. Surveys the current literature on computational, graph-theoretic approaches that use network algorithms for biological modeling, analysis, interpretation, and discovery. Enables hands-on experience in network biology by implementing computational projects.
BMI/COMPSCI 776: Advanced Bioinformatics
Credits unavailable
Advanced course covering computational problems in molecular biology. The course will study algorithms for problems such as: modeling sequence classes and features, phylogenetic tree construction, gene-expression data analysis, protein and RNA structure prediction, and whole-genome analysis and comparisons.
BMI/COMPSCI/ECE/MEDPHYS 722: Computational Optics and Imaging
Credits unavailable
Computational imaging includes all imaging methods that produce images as a result of computation on collected signals. Learn the tools to design new computational imaging methods to solve specific imaging problems. Provides an understanding of the physics of light propagation and measurement, and the computational tools to model it, including wave propagation, ray tracing, the radon transform, and linear algebra using matrix and integral operators and the computational tools to reconstruct an image, including linear inverse problems, neural networks, convex optimization, and filtered back-projection. Covers a variety of example computational imaging techniques and their applications including coded apertures, structured illumination, digital holography, computed tomography, imaging through scattering media, compressed sensing, and non-line-of-sight imaging.
BMI/COMPSCI/PSYCH 841: Computational Cognitive Science
Credits unavailable
Studies the biological and computational basis of intelligence, by combining methods from cognitive science, artificial intelligence, machine learning, computational biology, and cognitive neuroscience. Requires ability to program.
BMI/MEDICINE 918: Health Informatics for Medical Students Elective
2 credits
Biomedical Informatics is an interdisciplinary field that combines knowledge of information sciences and medical sciences to optimize the use and application of biomedical data across the spectrum from molecules to individuals to populations. Offers an overview of the field of health informatics by providing students with the fundamental knowledge of the concepts of health informatics and how technology can be used in the delivery of health care.
BMI/POPHLTH 451: Introduction to Sas Programming for Population Health
Credits unavailable
Use of the SAS programming language for the management and analysis of biomedical data.
BMI/POPHLTH 551: Introduction to Biostatistics for Population Health
4 credits
Designed for population health researcher. Topics include descriptive statistics, elementary probability, probability distributions, one- and two-sample normal inference (point estimation, hypothesis testing, confidence intervals), power and sample size calculations, one- and two-sample binomial inference, underlying assumptions and diagnostic work.
BMI/POPHLTH 552: Regression Methods for Population Health
Credits unavailable
Introduction to the primary statistical tools used in epidemiology and health services research: logistic regression for binary outcomes, multiple linear regression for continuous outcomes, multinomial regression models for categorical outcomes, and Poisson and negative binomial regression models for count outcomes.
BMI/POPHLTH 651: Advanced Regression Methods for Population Health
Credits unavailable
Extension of regression analysis to observational data with unequal variance, unequal sampling and propensity weights, clusters and longitudinal measurements, using different variance structures, mixed linear models, generalized linear models and GEE. Matrix notation will be introduced and underlying mathematical and statistical principles will be explained. Examples use data sets from ongoing population health research.
BMI/POPHLTH 661: Causal Inference, Surveys and Missing Data for Population Health
3 credits
Overview of modern statistical methods for dealing with "incomplete" data, including the design and analysis of complex surveys, the analysis of missing data, and causal inference.
BMI/POPHLTH 694: Applied Biomedical Informatics & Real-world Data for Precision Medicine & Population Health
Credits unavailable
Provides an introduction to key concepts, methods, and tools of biomedical and health informatics used in precision medicine and population health, with emphasis on collection, management, and analysis of real-world data.
BMI/STAT 541: Introduction to Biostatistics
3 credits
Course designed for the biomedical researcher. Topics include: descriptive statistics, hypothesis testing, estimation, confidence intervals, t-tests, chi-squared tests, analysis of variance, linear regression, correlation, nonparametric tests, survival analysis and odds ratio. Biomedical applications used for each topic.
BMI/STAT 542: Introduction to Clinical Trials I
Credits unavailable
Intended for biomedical researchers interested in the design and analysis of clinical trials. Topics include definition of hypotheses, measures of effectiveness, sample size, randomization, data collection and monitoring, and issues in statistical analysis.
BMI/STAT 620: Statistics in Human Genetics
Credits unavailable
Provides a comprehensive survey of statistical methods in human genetics research. Covered topics include linkage analysis, genome-wide association study, rare variant association analysis, meta-analysis, genome and variant annotation, heritability estimation, multi-trait modeling techniques, multi-omic data integration, and genetic risk prediction.
BMI/STAT 641: Statistical Methods for Clinical Trials
3 credits
Statistical issues in the design of clinical trials, basic survival analysis, data collection and sequential monitoring.
BMI/STAT 642: Statistical Methods for Epidemiology
Credits unavailable
Methods for analysis of case-control, cross sectional, and cohort studies. Covers epidemiologic study design, measures of association, rates, classical contingency table methods, and logistic and Poisson regression.
BMI/STAT 643: Clinical Trial Design, Implementation, and Analysis
Credits unavailable
Gain an understanding of fundamental elements of clinical trials (such as objectives, endpoints, surrogate endpoints, and statistical decisions) and statistical design considerations (such as randomization and blinding). Designs of clinical trials for Phase I, II, and III studies including single-arm, two-arm, and drug combination trials. Introduction to adaptive designs for precision medicine and master protocol designs such as umbrella trials and basket trials.
BMI/STAT 727: Theory and Methods of Longitudinal Data Analysis
Credits unavailable
Theory and methods of fundamental statistical models for the analysis of longitudinal data, including repeated measures analysis of variance, linear mixed models, generalized linear mixed models, and generalized estimating equations. Introduction of how to implement these methods in statistical softwares such as in R and/or SAS, within the context of appropriate statistical models and carry out and interpret analyses.
BMI/STAT 741: Survival Analysis Theory and Methods
Credits unavailable
Theory and practice of analytic methods for censored survival data, including nonparametric and parametric methods, the proportional hazards regression model, and a review of current topics in survival analysis.
BMI/STAT 768: Statistical Methods for Medical Image Analysis
3 credits
Introduce key statistical methods and concepts for analyzing various medical images. Analyze publicly available and student/instructor supplied imaging data using the most up-to-date methods and tools.
BMI/STAT 828: Semiparametric Methods in Data Science
Credits unavailable
Review of statistical convergence modes, M-estimation, and basics of Hilbert space. Introduction of how to derive the nuisance tangent space, its complement, and the corresponding efficient influence function, from the geometric perspective of semiparametric models. Introduction of how to estimate nuisance functions using machine learning methods, and their implementations in R and/or Python. Introduction of a variety of semiparametric models in missing data analysis, causal inference, dimension reduction, precision medicine, semi-supervised learning, transfer learning and domain adaptation.
BMI/STAT 877: Statistical Methods for Molecular Biology
Credits unavailable
Statistical and computational methods in statistical genomics for human and experimental populations. Review methods for quality control, experimental design, clustering, network analysis, and other downstream analysis of next-generation sequencing studies along with methods for genome wide association studies.