Thursday, February 25, 2021

A New OHSU Course in Applied Clinical Data Science and Machine Learning for Health & Clinical Informatics (HCIN) Students

I have written over the years about the need for all who work in biomedical and health informatics to have appropriate knowledge and skills in data science, machine learning (ML), artificial intelligence (AI), and related topics. I am now excited to announce that our OHSU Biomedical Informatics Graduate Program is launching a new course in Applied Clinical Data Science and Machine Learning for Health & Clinical Informatics (HCIN) majors.

The goal of this new course is not to provide students with the mastery of ML and AI tools and techniques; rather, it is to provide a conceptual understanding of their practical application in health and biomedicine. The course is not meant to be a substitute for the sequence of courses available in the other major in our program, Bioinformatics & Computational Biomedicine (BCB), whose offerings delve far more into the theory, mathematics, and programming of these topics and include:

  • BMI 551/651 - Statistical Methods
  • BMI 531/631 - Probability and Statistical Inference
  • BMI 543/643 - Machine Learning
  • BMI 525/625 - Principles and Practice of Data Visualization

The new HCIN course will be focused on applied data science and machine learning, with a focus on clinical data sets as well as clinical issues and challenges in their application. While the course will have some programming activity (requiring Python programming as a prerequisite), it will focus on a hands-on, high-level view of the different types of machine learning methods and their applications. It will also cover the topics of data management and selection, pitfalls in building and deploying models, and critical appraisal of clinical machine learning literature. The course will aim to provide an in-depth understanding for those who will work alongside experts who develop, build models, implement, and evaluate machine learning applications in health and clinical settings.

The textbook for the course will be: Hoyt, R. and Muenchen, R. (Eds.), 2019. Introduction to Biomedical Data Science, The course syllabus provides further details on the topics to be covered.

The content of the course will be based on a combination of what faculty and students believe is most important for a course like this. Among the topics that be included are:

  • Data sources - electronic health records, registries (e.g., N3C, AllOfUs), patient-generated, social media, public health
  • Data preparation (wrangling) - cleaning, quality analysis, feature selection, de-biasing
  • Exploratory data analysis - summaries, correlations, visualizations
  • Machine learning approaches and models - supervised, unsupervised, reinforcement, deep learning
  • Software and tools available
  • Common pitfalls and misunderstandings of applying machine learning
  • Critical appraisal of clinical machine learning literature
  • Ethical issues and challenges

The 3-credit course will be taught in the OHSU spring academic quarter, which runs from late March to early June. The lead instructors will be Steven Chamberlin, ND and myself, with other department faculty contributing. As with all courses in the HCIN major, it will be mostly online and asynchronous, with some option synchronous activities (which will be recorded for those not able to attend). This course will be different from to complementary to other data science-related courses in the HCIN major, including:

  • BSTA 525 - Introduction to Biostatistics
  • BMI 540/640 - Computer Science and Programming for Clinical Informatics
  • BMI 544/644 - Databases
  • BMI 524/624 - Data Analytics for Healthcare
  • BMI 516/616 - Standards/Interoperability in Healthcare
  • BMI 537/637 - Healthcare Quality
  • BMI 525/625 - Principles and Practice of Data Visualization

I will be excited to see how this course is accepted and how it evolves based on feedback of students and others. I suspect there will be interest beyond our graduate program.

Monday, February 22, 2021

Vaccinated and Vaccinating: The End May Be Near?

I was delighted to learn in early January that my institution, Oregon Health & Science University (OHSU), made the decision like many medical centers to offer the SARS-CoV-2 vaccine to all employees, not just those at the front line of care delivery. I received my first and second doses of the Pfizer vaccine on January 2nd and 23rd. I had some minor malaise the day after the second dose, but was thrilled to have received the vaccine.

I also decided that since I received an early dose, I would do everything I could to support the national and global effort to disseminate the vaccine. To that end, I have volunteered to work shifts at the OHSU Portland International Airport Vaccine Clinic. While I thought I might put my medical training to use giving injections, it turns out that the greater need was for registration and check-in personnel. I suppose it is most appropriate for the Chair of the informatics department to be checking in and scheduling follow-up appointments in Epic for those coming for their shots. But I actually enjoy the job I am doing at the site, interacting with people driving through the site and expressing gratitude they are able to get vaccinated. It is also nice to put on a friendly face for our university.

Overall, I feel a sense that the end may be near for the worst of this pandemic that has upended our lives. While the complete end will not come any time soon, and we will likely need to be vigilant about SARS-CoV-2 for years to come, I am hopeful that the vaccine rollout will continue at a strong pace and allow us to gradually resume more normal living. I am also encouraged that the COVID-19 numbers of cases, hospitalizations, and deaths are trending downward, and that we have new science-driven leadership in our federal government.

Looking ahead, I yearn to be around people at work, in social settings, and, yes, traveling. Regarding the latter, it has been almost a year since I have been on an airplane, although I am planning to visit my elderly stepfather, my last living adult relative, next month in Florida. He will have received his second dose a couple weeks before I visit.

There are many unanswered questions about what life will be like in the long run. Will work move to a more virtual arrangement? What will come of city centers that have been hurt by the pandemic and resulting economic and social upheaval? What will come of academic meetings and conferences, many of which probably could be done more virtually? Even though I spend a great deal of work time in front of a computer, I am still a social being. Social media has taken the sting off of the interpersonal isolation, but there is nothing like being around other people, and I am hopeful that much of that will eventually return. We will see as 2021 unfolds.