OHSU Online · School of Medicine
Sem:Appl Data Scien/Mach Learn
- Spring 2021
- 1-4 Credits
- 03/29/2021 to 06/18/2021
- Modified 03/18/2021
A current topics seminar that focuses on the topics of Biomedical Informatics. The instructor chooses the specific topics and schedules regular participation of the students.
Prerequisite: Consent of instructor
This syllabus is for BMI 507 OL Sp21, BMI 607 OL Sp21
Name: Steve Chamberlin, ND
Email: [email protected]
Address & Office Number: BICC
Office Hours: on request
Preferred Method of Contact: email
Expected Response Time: two business days
Name: William Hersh, MD
Email: [email protected]
Phone: 503-494-4563 (not routinely answered during pandemic; please use email)
Address & Office Number: BICC 517
Office Hours: on request
Preferred Method of Contact: email
Expected Response Time: two business days
Online course with occasional optional synchronous virtual sessions.
REQUIRED TEXTS OR READINGS
- R Hoyt and R Muenchen (eds.), Introduction to Biomedical Data Science, Lulu.com (available from lulu.com or amazon.com)
- R Hoyt and R Muenchen (eds.), Data Preparation and Exploration, Lulu.com (available from lulu.com or amazon.com)
SUPPLEMENTAL OR SUGGESTED READINGS OR REFERENCE MATERIALS
- A Geron, Hands-on Machine Learning with Scikit-Learn, Keras, & TensorFlow (available from amazon.com)
Course Competencies, Outcomes, and Objectives
By the end of the course, students will be able to:
- Apply machine learning techniques available and appropriate data sources that can be used with these techniques for different clinical domains.
- Critically assess literature and research for machine learning and its application to health care.
- Evaluate ethical considerations for machine learning and artificial intelligence.
- Address issues in health care with appropriate machine learning methods.
- Develop a machine learning solution to address an issue in healthcare.
- Make decisions about implementation and medical decision-making using machine learning models.
Grades are assigned based on the following criteria:
Grades will be based on scores from weekly assignments and a final project. The point breakdown is as follows:
Final Project 40%
Course & Instructor Evaluations
Complete instructions including required date of completion for each assignment is posted on Sakai learning portal. Please check regularly for updates as Sakai will have the most up to date information.
Week 1: Overview of biomedical data science.
General overview of biomedical data science: data analytical processes, major types of analytics, biomedical data science tools, and conflicting perspectives.
Week 2: Machine learning approaches and applications in different clinical domains.
Introduction to common machine learning algorithms used in different healthcare domains, model-based decision making, and successful model implementation strategies.
Week 3: Critical Appraisal of the ML Literature.
Critical appraisal of machine learning literature to help inform new model applications and assess needs in healthcare.
Week 4: Databases, data sources, programming languages, ML tools, big data.
Introduction to data base models, appropriate data for machine learning models, available public data sources, programming languages and automated tools for machine learning model development and issues with ‘Big Data.’
Week 5: Data preparation.
Reading raw data, file formats, data reshaping and combining, general inspection and descriptive statistics, data cleanup, data leakage and missing data.
Week 6: Exploratory Data Analysis: data exploration and visualization.
Data visualization tools, variable correlation, evaluating distributions and model assumptions, assessing outliers and influential observations. Automated tools will be introduced for some of these tasks.
Week 7: Model development and evaluation using an automated tool, PART 1.
Application of basic machine learning techniques to a problem in healthcare, including evaluation of predictive analytical performance and best model selection.
Week 8: Model development and evaluation using an automated tool, PART 2.
Introduction to more complex machine learning methods, such as neural networks, deep learning, natural language processing and language models (Bert, transformers, neural network approaches to natural language processing).
Week 9: Model implementation.
Aspects of model implementation in a clinical setting, such as decision making with the model, impact prediction, platforms for implementation, explanation of model recommendations, model support after implementation.
Week 10: Ethics
Ethical issues in machine learning and artificial intelligence, such as misuse of data and algorithms, impact on health disparities, democratization of artificial intelligence, replacing human decision making with automated decision making.
Course Policies and Resources
Course is delivered in asynchronous online format but students must meet deadlines for course activities and assignments.
School Policies and Resources
Graduate Studies Guidelines:
Students are responsible for following all OHSU School of Medicine, Graduate Studies, and program/department guidelines & policies. For more information, please visit here. For program/department guidelines & policies, please inquiry with the program/department director and/or coordinator.
School of Medicine Conduct Policy (housed under the graduate studies guidelines section)
Students are responsible for their own academic work. Students are expected to have read and practice principles of academic honesty, as presented in the Graduate Studies Student Handbook.
The School of Medicine reserves the privilege of retaining only those students who, in the judgement of the faculty, satisfy the requirements of scholarship and clinical performance necessary to maintain the highest standards. The Student Handbook has information about academic standards and probation and dismissal policies.
Grading Criteria, Academic Standards, & Release of Final Grades:
Graduate Studies in the OHSU School of Medicine is committed to providing grades to students in a timely manner. Course instructors will provide students with information in writing at the beginning of each course that describes the grading policies and procedures including but not limited to evaluation criteria, expected time needed to grade individual student examinations and type of feedback they will provide.
All coursework applied towards degree requirements must meet the minimum cumulative grade point average of at least 3.0.
Refer to the School of Medicine Graduate Studies Forms & Policies for withdraw, incomplete, and in-progress grading standards. Final course grades will be posted with the OHSU Registrar the Monday following the last day of the term. On those occasions when a grade has not been submitted by the deadline, the following procedure shall be followed:
- The Department*/Program** Coordinator will immediately contact the Instructor requesting the missing grade, with a copy to the Program Director and Registrar.
- If the grade is still overdue by the end of next week, the Department*/Program** Coordinator will email the Department Chair directly, with a copy to the Instructor and Program Director requesting resolution of the missing grade.
- If, after an additional week the grade is still outstanding, the student or Department*/Program** Coordinator may petition the Office of Graduate Studies for final resolution.
*For courses that are run by a specific department.
**For the conjoined courses (course number is preceded by CON) that are run by Graduate Studies.
Graduate Studies Inclement Weather Procedures
Inclement weather procedures can be found here. In the case of inclement weather, the faculty member will email or place a voice-mail greeting on her/his office telephone number by 6:00am on the day of the clinical or class to give instructions to students about the class schedule.
Graduate Studies Copyright Information
Every reasonable effort has been made to protect the copyright requirements of materials used in this course. Class participants are warned not to copy, audio, or videotape in violation of copyright laws. Journal articles will be kept on reserve at the library or online for student access. Copyright law does allow for making one personal copy of each article from the original article. This limit also applies to electronic sources.
DMICE Communication Policy
- If the syllabus directs the student to contact the TA before contacting the instructor, the student should do so. Otherwise, the student should contact the instructor and allow 2 business days (not including weekends) for a response.
- If the student does not receive a response from the instructor within 2 business days, s/he should contact the TA (if there is one). When contacting the TA s/he should cc the instructor and Diane Doctor at [email protected].
- If a student does not receive a response from the TA within 1 business day (not including weekends), s/he should contact Diane Doctor at [email protected] and cc the instructor and the TA.
- If Diane does not reply within 1 business day (not including weekends), the student should contact Andrea Ilg at [email protected].
- Students having difficulties with Sakai should contact the Sakai Help Desk at [email protected] or at (877) 972-5249. Sakai help is available M-F from 8am to 10-pm and weekends from Noon to 5pm. Do not contact the instructor.
When Problems Arise
It is critical to contact the appropriate person when problems arise:
- For basic Sakai problems and course issues (e.g., cannot log in, after-hours technical assistance, Course Materials or Forum not available/accessible during regular business hours/days), contact the Sakai Help Desk: Toll-Free - (877) 972-5249; email - [email protected]. Sakai help is available M-F from 8 am to 9 pm and weekends from Noon to 5pm.
- For questions about course content (e.g., do not understand a topic or disagree with homework quiz answer), contact the Teaching Assistant, who will be announced at the beginning of the course: go to the Email Tab after logging into the course and choose “Associate” role to send message to the TA or post a question in the Forums.
It is OHSU policy that any exam offered online and worth more than 10% of the final course grade must be virtually proctored. In this course, we will be using the services of Examity, a remote proctoring services company. You will be required to schedule your exam three (3) weeks ahead of time. There is no cost to the student. More information will be provided to you regarding setup, scheduling, and requirements in the Course Materials.
Turn It In
In an effort to uphold the principles and practice of academic honesty, faculty members at OHSU may use originality checking systems such as Turnitin to compare a student’s submitted work against multiple sources. To protect student privacy in this process, it will be necessary to remove all personal information, i.e. student name, email address, student u-number, or any other personal information, from documents BEFORE submission.
Sakai and TLC Help Desk
You will learn through the Sakai learning management software at http://sakai.ohsu.edu. The online component includes reading material, lectures (including streaming presentations and handouts), project material, learning assignments, and online discussions. If you have any technical questions or if you need help logging in, please contact the Sakai Help Desk, which is open Mon – Fri, 8 am – 9 pm and weekends 12 pm – 5 pm, Pacific Time.
(Email) [email protected]
Please use professional etiquette when communicating with peers and the instructor. This means avoiding aggressive or offensive language, showing respect for others’ opinions and positions, and conducting yourself as if you were face to face with them. Please pay special attention to etiquette in class forums and when using email. If you notice someone violating this policy, please make the instructor and TA aware of the problem.
Respect for all App.
OHSU’s Respect for All app helps students, faculty, and staff educate themselves about sexual misconduct and harassment as well as their reporting responsibilities. To download the app, open the link below in Chrome, Firefox, Edge, Safari or Opera. It does not work in Internet Explorer.
List of OHSU Graduation Core Competencies
- Professional Knowledge and Skills
- Information Literacy
- Community Engagement, Social Justice and Equity
- Patient Centered Care
To access a descriptive list of OHSU Graducation Core Competencies: OHSU Graduation Core Competencies
Institutional Policies and Resources
Statement Regarding Students with Disabilities:
OHSU is committed to inclusive and accessible learning environments in compliance with federal and state law. If you have a disability or think you may have a disability (mental health, attention-related, learning, vision, hearing, physical or health impacts) contact the Office for Student Access at (503) 494-0082 or OHSU Student Access to have a confidential conversation about academic accommodations. Information is also available at Student Access Website. Because accommodations may take time to implement and cannot be applied retroactively, it is important to have this discussion as soon as possible.
Student Evaluation of Courses:
Course evaluation results are extremely important and used to help improve courses and the learning experience of future students. Responses will always remain anonymous and will only be available to instructors after grades have been posted. The results of scaled questions and comments go to both the instructor and their unit head/supervisor. Refer to Student Evaluation of Courses and Instructional Effectiveness, *Policy No. 02-50-035.
*To access the OHSU Student Evaluation of Courses and Instructional Effectiveness Policy, you must log into the OHSU O2 website.
Copyright laws and fair use policies protect the rights of those who have produced the material. The copy in this course has been provided for private study, scholarship, or research. Other uses may require permission from the copyright holder. The user of this work is responsible for adhering to copyright law of the U.S. (Title 17, U.S. Code). To help you familiarize yourself with copyright and fair use policies, the University encourages you to visit its Copyright Web Page
Sakai course web sites contain material protected by copyrights held by the instructor, other individuals or institutions. Such material is used for educational purposes in accord with copyright law and/or with permission given by the owners of the original material. You may download one copy of the materials on any single computer for non-commercial, personal, or educational purposes only, provided that you (1) do not modify it, (2) use it only for the duration of this course, and (3) include both this notice and any copyright notice originally included with the material. Beyond this use, no material from the course web site may be copied, reproduced, re-published, uploaded, posted, transmitted, or distributed in any way without the permission of the original copyright holder. The instructor assumes no responsibility for individuals who improperly use copyrighted material placed on the web site.
Syllabi Changes and Retention:
Syllabi are considered to be a learning agreement between students and the faculty of record. Information contained in syllabi, other than the minimum requirements, may be subject to change as deemed appropriate by the faculty of record in concurrence with the academic program and the Office of the Provost. Refer to the *Course Syllabi Policy, 02-50-050.
*To access the OHSU Course Syllabus Policy, you must log into the OHSU O2 website.
Commitment to Diversity & Inclusion:
OHSU is committed to creating and fostering a learning and working environment based on open communication and mutual respect. If you encounter sexual harassment, sexual misconduct, sexual assault, or discrimination based on race, color, religion, age, national origin, veteran’s status, ancestry, sex, marital status, pregnancy or parenting status, sexual orientation, gender identity, disability or any other protected status please contact the Affirmative Action and Equal Opportunity Department at 503-494-5148 or [email protected]. Inquiries about Title IX compliance or sex/gender discrimination and harassment may be directed to the OHSU Title IX Coordinator at 503-494-0258 or [email protected].
Modified Operations, Policy 01-40-010:
Portland Campus: Marquam Hill and South Waterfront
Students should review O2 or call OHSU’s weather alert line at 503-494-9021 for the most up-to-date information on OHSU-wide modified operations which include but are not limited to delays or closures for inclement weather.
If your home institution is not on the Portland campus (Marquam Hill or South Waterfront, contact your home institution for more information.
OHSU Resources Available to Students*:
Remote Learning Resources
The Remote Learning webpage on O2 contains concise, practical resources, and strategies for students that need to quickly transition to a fully remote instructional format.
Mackenzie Hall, Rm. 1120
503-494-7800; Email the Registrar
Student Registration Information:
To Register for Classes
OHSU ITG Help Desk
Regular staff hours are 6 a.m. to 6 p.m., Monday through Friday, but phones are answered seven days a week, 24 hours a day. Call 503 494-2222.
Teaching and Learning Center
Academic Support Counseling and Sakai Course Management System, please contact the TLC Help Desk at 877-972-5249 or email TLC Help Desk
Student Academic Support Services
For resources on improving student’s study strategies, time management, motivation, test-taking skills and more, Please access the Student Academic Support Services Sakai page. For one-on-one appointments or to arrange a workshop for students, please contact Emily Hillhouse.
Concourse Syllabus Management
For help with accessing your Concourse Syllabus: Please contact the Sakai help Desk for all other Concourse inquiries please visit the Concourse resources website or please contact the Mark Rivera at [email protected] or call 503-494-0934
- Emergency on Campus: 503-494-4444 (Portland)
- Non-emergency: 503-494-7744; Contact Public Safety
Student Health & Wellness Center
Baird Hall, Rm. 18 (Primary Care) and Rm. 6 (Behavioral Health)
503-494-8665; For urgent care after hours, 503-494-8311 and ask for the Nurse on call.
Wellness Center Information
Wellness Center Website
If your home institution is not on the Portland campus, contact your home institution student support services for more information.
Library: Biomedical Information Communication Center
BICC Library Hours of Operation
Privacy While Learning Remotely
Students may be asked to take classes remotely through videoconferencing software like WebEx. Some of these remote classes will be recorded. Any recording will capture the presenter’s audio, video, and computer screen. Student video and audio will be recorded if and when you unmute your audio and share your video during the recorded sessions. These recordings will not be shared with or accessible to the public without prior written consent.