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Health Informatics (HINF) Courses

Academic Unit: Health Informatics, AHC Inst

HINF 5115 - Interprofessional Healthcare Informatics (Primarily Online)

(3 cr; Prereq-Grad student or professional student or instr consent; Student Option; offered Every Fall, Spring & Summer)

Implications of informatics for practice, including nursing, public health, and healthcare in general. Electronic health record issues. Relates ethical, legislative and political issues informatics. Global and future informatics issues.

HINF 5394 - Directed Research

(1 cr [max 6]; Student Option No Audit; offered Periodic Fall, Spring & Summer; may be repeated for 18 credits; may be repeated 3 times)

Directed research arranged with faculty member.

HINF 5430 - Foundations of Health Informatics I

(3 cr; Prereq-Junior, senior, grad student, professional student, or instr consent; Student Option; offered Every Fall & Spring)

An introductory survey of health informatics, focusing on foundational concepts. Topics covered include: conceptualizations of data, information, and knowledge; current terminologies, coding, and classification systems for medical information; ethics, privacy, and security; systems analysis, process and data modeling; human-computer interaction and data visualization. Lectures, readings, and exercises highlight the intersections of these topics with electronic health record systems and other health information technology.

HINF 5431 - Foundations of Health Informatics II

(3 cr; Prereq-Junior, senior, grad student, professional student, or instr consent; Student Option; offered Every Spring)

An introductory survey of health informatics, focusing on applications of informatics concepts and technologies. Topics covered include: health informatics research, literature, and evaluation; precision medicine; decision models; computerized decision support systems; data mining, natural language processing, social media, rule-based system, and other emerging technologies for supporting 'Big Data' applications; security for health care information handling. Lectures, readings, and exercises highlight the intersections of these topics with current information technology for clinical care and research.

HINF 5436 - AHC Informatics Grand Rounds

(1 cr; A-F or Audit; offered Every Fall; may be repeated for 10 credits; may be repeated 10 times)

Presentation/discussion of research problems, current literature/topics of interest in Health Informatics.

HINF 5440 - Foundations of Translational Bioinformatics

(3 cr; A-F or Audit; offered Every Spring)

Translational bioinformatics deals with the assaying, computational analysis and knowledge-based interpretation of complex molecular data to better understand, prevent, diagnose and treat disease. This course emphasizes deep DNA sequencing methods that have persistent impact on research related to disease diagnosis and treatment. The course covers sequence analysis, applications to genome sequences, and sequence-function analysis, analysis of modern genomic data, sequence analysis for gene expression/functional genomics analysis, and gene mapping/applied population genetics. Prerequisites: MS, PhD, or MD/PhD student interested in translational bioinformatics

HINF 5450 - Foundations of Precision Medicine Informatics

(3 cr; Student Option; offered Periodic Fall)

The course will provide an introduction into the fundamental concepts of Precision Medicine with a focus on informatics-focused applications for clinical data representation, acquisition, decision making and outcomes evaluation. The student will gain an appreciation of fundamental biomedical data representation and its application to genomic, clinical, and population problems.

HINF 5494 - Topics in Health Informatics (Topics course)

(1 cr [max 3]; Prereq-Professional student or grad student or instr consent; Student Option; offered Periodic Fall & Spring; may be repeated for 9 credits; may be repeated 3 times)

Topics in health informatics.

HINF 5496 - Internship in Health Informatics

(1 cr [max 6]; Prereq-HINF student or instr consent; S-N or Audit; offered Every Fall, Spring & Summer; may be repeated for 18 credits; may be repeated 3 times)

Practical industrial experience not directly related to student's normal academic experience.

HINF 5499 - Capstone Project for the Masters of Health Informatics

(3 cr; Prereq-second semester MHI student or instr consent; S-N only; offered Every Fall, Spring & Summer)

Final opportunity to apply newly acquired knowledge/skills to project involving practical problem in health informatics. Submit written project report in lieu of final examination.

HINF 5501 - US Health Care System: Information Challenges in Clinical Care

(1 cr; Prereq-Junior or senior or professional student or grad student or instr consent; S-N or Audit; offered Every Fall & Spring)

Health care system/its unique interaction between key health system stakeholders. Relationship between patients, providers, payers, regulatory bodies. Role of information management/challenges of information standardization/exchange.

HINF 5502 - Python Programming Essentials for the Health Sciences

(1 cr; Prereq-Junior or senior or grad student or professional student or instr consent; S-N or Audit; offered Every Fall & Spring)

Computer programming essentials for health sciences/health care applications using Python 3. Intended for students with limited programming background, or students wishing to obtain proficiency in Python programming language.

HINF 5510 - Applied Health Care Databases: Database Principles and Data Evaluation

(3 cr; Prereq-Junior or senior or grad student or professional student or instr consent; A-F or Audit; offered Every Fall)

Principles of database theory, modeling, design, and manipulation of databases will be introduced, taught with a healthcare applications emphasis. Students will gain experience using a relational database management system (RDBMS), and database manipulation will be explored using Structured Query Language (SQL) to compose and execute queries. Students will be able to critically evaluate database query methods and results, and understand their implications for health care.

HINF 5520 - Informatics Methods for Health Care Quality, Outcomes, and Patient Safety

(2 cr; Prereq-Junior or senior or grad student or professional student or instr consent; Student Option; offered Every Spring)

Application/operation of clinical information systems, electronic health records, decision support/application in health care system. Use of clinical information systems/association with health care delivery, payment, quality, outcomes.

HINF 5530 - Health Care Software Management (Primarily Online)

(2 cr; Prereq-HINF student or instr consent; A-F or Audit; offered Every Spring)

Health care software and unique interaction between key stakeholders in health care software development and implementation. Systems analysis, software development, and software life cycle management for health care applications.

HINF 5531 - Health Data Analytics and Data Science

(3 cr; Prereq-Junior or senior or professional student or grad student or instr consent; A-F or Audit; offered Every Spring)

Data science methods and techniques for the extraction, preparation, and use of health data in decision making.

HINF 5540 - Interprofessional Health Informatics

(2 cr; A-F only; offered Every Spring)

Informatics applications in various healthcare professions. Clinical specialties. Informatics tools to improve healthcare services/outcomes through lectures/presentations.

HINF 5610 - Foundations of Biomedical Natural Language Processing

(3 cr; Student Option; offered Periodic Fall)

The course will provide a systematic introduction to basic knowledge and methods used in natural language processing (NLP) research. It will introduce biomedical NLP tasks and methods as well as their resources and applications in the biomedical domain. The course will also provide hands-on experience with existing NLP tools and systems. Students will gain basic knowledge and skills in handling with main biomedical NLP tasks. Prerequisites graduate student or instructor consent; Experience with at least one programming language (Python or Perl preferred) Recommended: basic understanding of data mining concepts, basic knowledge of computational linguistics

HINF 5620 - Data Visualization for the Health Sciences

(3 cr; A-F or Audit; offered Periodic Spring)

An advanced health informatics course, focusing on theoretical and practical aspects of data and information visualization for health care and the health sciences. Topics include classic and novel visualization types; models of human visual perception and cognition; color, text and typography; maps and diagrams; evaluation and testing; and the aesthetic and cultural aspects of visualization. Examples emphasize health sciences applications for clinicians, patients, researchers, and analysts. Modern programming and commercial tools are discussed, including D3, ggplot2, and Tableau. Students will report on and discuss visualization methods, published studies and books, culminating in a final visualization project of the student's choosing.

HINF 5630 - Clinical Data Mining

(3 cr; Student Option No Audit; offered Periodic Fall)

This is a hands-on introductory data mining course specifically focusing on health care applications. Analogously to the relationship between biostatistics and statistics, the data and computational challenges, the experiment design and the model performance requirements towards data mining in the clinical domain differ from those in general applications. This course aims to teach the students the most common data mining techniques and elaborate on the differences between general and clinical data mining. Specifically, the course will focus on (i) clinical data challenges and preprocessing; (ii) survey of the most common techniques in the clinical domain; (iii) clinical application touching up on experimental design and collaborations with physicians. The class will meet twice a week, one day dedicated to lectures and one day to a hands-on lab component, where students are expected to apply the techniques to health-related data. Some of the models will be evaluated with the involvement of a physician collaborator. Prerequisites: Basic linear algebra (matrix notation), basic optimization (gradient descent) Graduate level introductory statistics (e.g. STAT 5101-5102) or equivalent or instructor consent

HINF 5640 - Advanced Translational Bioinformatics Methods

(3 cr; A-F or Audit; offered Every Fall)

This course is designed to introduce the high throughput platforms to students who are interested in the genomics research and genomics data analysis in the basic and clinical medical science field. The course covers history of the genomics platforms, its revolution and the specifics of the data generated by all existing different platforms. The course will also introduce all existing sequencing platforms and applications to biological science, as well the current trends in this field.

HINF 5650 - Integrative Genomics and Computational Methods

(3 cr; A-F or Audit; offered Periodic Spring)

Genome-scale high throughput data sets are a central feature of modern biological research and translational clinical study. Experimental, computational biologists and clinical researchers who want to get the most from their data sets need to have a firm grasp and understanding of genomic data structure characteristics, analytical methodology and the intrinsic connection to integrate. This course is designed to build competence in quantitative methods for the analysis of high-throughput genomic data and data integration.

HINF 5660 - Applied Causal Discovery

(3 cr; Student Option; offered Every Spring)

Which genes cause cancer? Does cholesterol cause heart attacks? Computational causal discovery (especially from observational data) is a recently developed and developing field at the intersection of statistics and machine learning, with numerous and important untapped applications in scientific and medical research. This course provides a foundation for students to go on to apply causal discovery methods to their own data sets. The focus of this course is on developing the students? ability to identify when and why to use computational causal discovery methods, how to determine what methods are appropriate to use in a given context, and how to interpret and report the results. Students in this course will gain hands-on experience applying causal discovery algorithms, develop an understanding of the computational challenges one faces when using causal discovery algorithms, and learn the best practices for using causal discovery algorithms.

HINF 8220 - Computational Causal Analytics

(3 cr; A-F or Audit; offered Every Spring)

Identifying causal relationships and mechanisms is the ultimate goal of natural sciences. This course will introduce concepts and techniques underlying computational causal discovery and causal inference utilizing both observational and experimental data. Example applications of the above mentioned techniques in the domain of health sciences include reconstructing the molecular pathways underlying a particular disease, identifying the complex and interacting factors influencing a mental health disorder, and evaluating the potential impact of a public health policy. The course emphasizes both on the theoretical foundations and the practical aspects of causal discovery and causal inference. Students will gain hands-on experience with applying major causal discovery algorithms on simulated and real data.

HINF 8333 - FTE: Master's

(1 cr; Prereq-Master's student, adviser and DGS consent; No Grade Associated; offered Every Fall, Spring & Summer; 6 academic progress units; 6 financial aid progress units)

(No description)

HINF 8405 - Advanced Topics in Health Informatics I (Topics course)

(1 cr [max 4]; Prereq-Professional student or grad student or instr consent; Student Option; offered Every Fall; may be repeated for 12 credits; may be repeated 3 times)

Topics may include computer systems design for health sciences, small computer concepts/use, computers for clinical services, computer-aided medical decision making, biomedical image processing, pattern recognition, data mining. Case studies from health sciences.

HINF 8406 - Advanced Topics in Health Informatics II (Topics course)

(1 cr [max 4]; Student Option; offered Every Spring; may be repeated for 12 credits; may be repeated 3 times)

This is a topics course. Topics may include, computational causal discovery for health sciences, computer systems design for health sciences, small computer concepts and use, computers for clinical services, computer-aided medical decision making, biomedical image processing, and pattern recognition. Case studies from health sciences.

HINF 8430 - Foundations of Health Informatics I Lab

(2 cr; A-F or Audit; offered Every Fall)

The PhD-level lab complement for introductory survey of health informatics, focusing on foundational concepts. Topics covered include: conceptualizations of data, information, and knowledge; current terminologies, coding, and classification systems for medical information; ethics, privacy, and security; systems analysis, process and data modeling; human-computer interaction and data visualization. Lectures, readings, and exercises highlight the intersections of these topics with electronic health record systems and other health information technology.

HINF 8431 - Foundations of Health Informatics II Lab

(2 cr; Student Option; offered Every Spring)

The PhD-level lab complement for an introductory survey of health informatics, focusing on applications of informatics concepts and technologies. Topics covered include: health informatics research, literature, and evaluation; precision medicine; decision models; computerized decision support systems; data mining, natural language processing, social media, rule-based system, and other emerging technologies for supporting 'Big Data' applications; security for health care information handling. Lectures, readings, and exercises highlight the intersections of these topics with current information technology for clinical care and research.

HINF 8434 - Medical Decision Support Techniques

(3 cr; A-F or Audit; offered Every Fall & Spring)

Examines systems based on statistical and logical approaches to decision making that include statistical prediction, rule-based systems, case-based reasoning, quantitative reasoning, and neural networks, and issues related to their use.

HINF 8440 - Foundations of Translational Bioinformatics Lab

(2 cr; A-F or Audit; offered Every Spring)

Translational bioinformatics deals with the assaying, computational analysis and knowledge-based interpretation of complex molecular data to better understand, prevent, diagnose and treat disease. This course emphasizes deep DNA sequencing methods that have persistent impact on research related to disease diagnosis and treatment. The course covers sequence analysis, applications to genome sequences, and sequence-function analysis, analysis of modern genomic data, sequence analysis for gene expression/functional genomics analysis, and gene mapping/applied population genetics. Prerequisites: MS, PhD, or MD/PhD student interested in translational bioinformatics

HINF 8444 - FTE: Doctoral

(1 cr; Prereq-Doctoral student, adviser and DGS consent; No Grade Associated; offered Every Fall, Spring & Summer; 6 academic progress units; 6 financial aid progress units)

(No description)

HINF 8492 - Advanced Readings or Research in Health Informatics

(1 cr [max 6]; Prereq-HINF student or instr consent; Student Option No Audit; offered Every Fall, Spring & Summer; may be repeated for 24 credits; may be repeated 4 times)

Directed readings or research in topics of current or theoretical interest in health informatics.

HINF 8494 - Research in Health Informatics

(1 cr [max 6]; Prereq-instr consent; A-F or Audit; offered Every Fall, Spring & Summer; may be repeated for 6 credits)

Directed research under faculty guidance.

HINF 8525 - Health Informatics Teaching

(2 cr; Prereq-HINF student or instr consent prereq: HINF student or instr consent; A-F only; offered Spring Even Year)

Use selected teaching techniques to assist in the delivery of course content in health informatics curriculum. Work with a professor who is the course director. From evaluation and feedback on their teaching technique, students develop a teaching philosophy as a final course project.

HINF 8535 - Advanced Health Informatics Research Methods

(3 cr; Prereq-HINF student or instr consent; A-F only; offered Spring Even Year)

Application of research methods, evaluation. Design, data collection, and data analysis in the context of health informatics, including computational and health data challenges.

HINF 8666 - Doctoral Pre-Thesis Credits

(1 cr [max 6]; Prereq-Doctoral student who has not passed prelim oral; no required consent for 1st/2nd registrations, up to 12 combined cr; dept consent for 3rd/4th registrations, up to 24 combined cr; doctoral student admitted before summer 2007 may register up to four times, up to 60 combined cr; No Grade Associated; offered Every Fall, Spring & Summer; may be repeated for 12 credits; may be repeated 2 times)

TBD

HINF 8770 - Plan B Project

(4 cr; Prereq-Advanced plan B MS student; No Grade Associated; offered Every Fall, Spring & Summer)

Research project. Topic arranged between student/instructor. Written report required.

HINF 8777 - Thesis Credits: Master's

(1 cr [max 18]; Prereq-Max 18 cr per semester or summer; 10 cr total required [Plan A only]; No Grade Associated; offered Every Fall, Spring & Summer; may be repeated for 50 credits; may be repeated 10 times)

(No description)

HINF 8888 - Thesis Credit: Doctoral

(1 cr [max 24]; Prereq-PhD candidate or department consent. Max 18 credits per semester; 24 credits required; No Grade Associated; offered Every Fall, Spring & Summer; may be repeated for 100 credits; may be repeated 10 times)

(No description)

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