PQHS 416 is course that introduces students to computational techniques and concepts that underpin biomedical and health informatics data management and analysis. In particular, the course will focus on the three topics of: (1) Biomedical terminologies and formal logic used in building knowledge models such as ontologies; (2) Natural language processing (NLP), and (3) Big Data technologies, including components of Hadoop stack and Apache Spark. This is a lecture-based course that relies on both materials covered in class and out-of-class readings of published literature. Students will be assigned reading assignments, homework exercise assignments and they are expected to complete homework assignment for each class. The students will be involved in a team project and they will be expected to prepare a project report at the end of the semester.
|#||Competency||Learning Outcomes||Assignments and Assessment|
|1||Understand the fundamentals of using biomedical ontologies for integration of biomedical and health data||
||In-class lectures will cover ontology engineering to develop formal knowledge models of biomedical domains and principles of data integration. Students are required to complete homework assignments for each class topic and review published articles describing the use of biomedical ontologies in data integration applications|
|2||Understand the components of natural language processing workflow for unstructured biomedical text||
||In-class lectures will cover fundamentals of natural language processing. The students are required to complete homework assignments for each class topic and review published articles describing the use of natural language processing tools for unstructured and semi-structured biomedical text|
|3||Understand the concept of Big Data and use of Big Data technologies to address data processing and analysis challenges||Can use Big Data tool library for processing and analyzing data||In-class lectures will cover concepts of Big Data technologies and demonstrate the use of these technologies for data processing as well as analysis|
Undergraduate and Graduate students are expected to completed coursework in programming, data processing, and data management with an understanding of biomedical and health systems, including electronic health record systems
Based on the university policy, students need to register and drop/add the course within a one-week period at the start of the course
The focus of the course is on hands-on training of students in three core components of computing techniques in biomedical and health informatics. This is an active-learning class and readings, class exercises, and homework assignments will be assigned. Students are expected to complete the assignments before coming to class. Class participation is an essential component of this class and this is part of the student assessment in this class. In addition, homework assignments, mid-term examination, and final project report as well as presentation will be used to assess students. In class exercises may be assigned before class and students are expected to follow directions in Canvas to complete these exercises. The final exam will be based on the team project and involve presentation and a project report for evaluation.
There is no required textbook for this course. Topic-specific reading material will be listed as part of the course work
Homework will be assigned after each lecture. Students are expected to complete the assignment and turn them in to the instructor at the start of the next class
Students are expected to attend all classes
Students with a disability—please make an appointment with the instructor to discuss your needs at the earliest convenience. The necessary adjustments will be provided to facilitate the learning experience. Additionally, please be in contact with the Coordinator of Disability Resources, Educational Services for Students (ESS). ESS is located in 470 Sears Building. The office phone number is 216-368-5230, and the website is here
Although having a laptop in class opens up new learning possibilities for students, it can be used in ways that are inappropriate. It is easy for your laptop to become a distraction to you and to those around you. Laptops are to be used only when essential to the task at hand. Please turn off or silence all cell/smart phones, tablets, and other electronic devices for the duration of the course. Inappropriate uses will be noted and may affect the final grade.
All forms of academic dishonesty including cheating, plagiarism, misrepresentation, and obstruction are violations of academic integrity standards. Cheating includes copying from another's work, falsifying problem solutions or laboratory reports, or using unauthorized sources, notes or computer programs. Plagiarism includes the presentation, without proper attribution, of another's words or ideas from printed or electronic sources. It is also plagiarism to submit, without the instructor's consent, an assignment in one class previously submitted in another. Misrepresentation includes forgery of official academic documents, the presentation of altered or falsified documents or testimony to a university office or official, taking an exam for another student, or lying about personal circumstances to postpone tests or assignments. Obstruction occurs when a student engages in unreasonable conduct that interferes with another's ability to conduct scholarly activity. Destroying a student's computer file, stealing a student's notebook, and stealing a book on reserve in the library are examples of obstruction.