DS BMED 208
Recent Research in Machine Learning in Medicine
Lecture.
Fall 2026: 3 sections. Nothing here is open. The oldest of these readings was 15 minutes ago.
Grades
3.94
Average grade awarded in DS BMED 208. Not a student rating: this is what the grades were.
In the A range
98%
of the 63 letter grades
D, F or W
1.6%
of every letter grade awarded, plus withdrawals
Taken pass/no pass
-
the registrar has this letter grade only this term
The registrar's own records: 63 grades over 2 terms, Fall 2021 to Fall 2025. Every instructor is pooled here.
What is inside that record
No summer session is in that record.
The table below splits them, and term averages across those 2 terms ran 3.89 to 4.00.
Historical grades for ERNST, JASON, across recorded terms. The course summary above includes all professors.
- A 33 · 97.1%
- F 1 · 2.9%
Percentages are of the 34 letter grades. Grey bars are non-letter outcomes.
How the non-letter outcomes are counted
They are excluded from the GPA entirely rather than scored, because counting a P as a 4.0 would be a fabrication.
By instructor
| Instructor | Predicted GPA | Raw | n | Terms | A range | Workload | Fall 2026 |
|---|---|---|---|---|---|---|---|
| ERNST, JASON reviews ↗ | 3.90 | 3.88 | 34 | 2 | 97% | - | Closed by the department |
| CHIANG, JEFFREY NIEN-JAY reviews ↗ | 3.97 | 4.00 | 29 | 2 | 100% | - | not teaching it |
Why Predicted is not the Raw average
“Predicted” is shrunk toward the course average, which is itself shrunk toward the department, so an instructor with a handful of students sits near the course mean rather than topping the list.
Grade records describe outcomes. For what a course is like to take, read student reviews written on dibs below or follow the separate external review link.
Workload and assignments
Work types reported in BruinWalk reviews of this course, across recorded instructors and terms. They may differ from this term's syllabus.
dibs has not read this course’s reviews, so it cannot say what kind of work it sets. That is dibs not having looked. It is not a course without papers or exams, and the reviews linked below are the answer until dibs catches up.
From the registrar's catalog
Lecture, four hours; discussion, two hours. Requisite: course 200 or equivalent. Overview of recent research in machine learning applied to medicine. Covers recent papers utilizing data science approaches to analyze large amounts of medical data. Topics include analysis of medical imaging data, electronic health records, and waveforms. Students receive instruction on how to read recent research papers, and present these papers in class. May be repeated twice for credit. Letter grading.
Sections in Fall 2026
Seat counts as of : the oldest of these 3 readings. Seat readings are snapshots, not live availability. Their timestamps show when dibs last checked.
-
Lec 1 W 5:00pm-5:50pmClosed by the department
Rudas, A. and Lee, S.A.
3.93predicted, all instructors · 63 grades8 enrolled no history
-
Lec 2 W 5:00pm-6:00pm, R 9:00am-10:00am, F 12:00pm-1:00pmClosed by the department
Ernst, J. and Efrat, L.
3.90predicted, this instructor · 34 grades11 enrolled no history
-
Lec 3 W 5:00pm-5:50pmClosed by the department
Rudas, A. and Lee, S.A.
3.93predicted, all instructors · 63 grades15 enrolled no history
Final enrollment, averaged across each term's sections: between 14 and 18 a term over 2 terms, summer excluded, most recently 14 in Fall 2025. That is the shape across years, not this term, which is above.
From the people who took it
Student reviews
What taking DS BMED 208 was like: the work, the teaching, and what students wish they’d known.
Your experience could be the first.
No student reviews are available to read on dibs for this course yet. Took it? Tell the next person what helped, what was hard, and how you spent your time.
Looking for more perspectives?
External reviews are separate and do not count toward the dibs rating.
Seats over time in Fall 2026
How each lecture has filled since dibs first saw it. This course runs 3 lectures; the legend under the chart picks one.
A dot is a reading where something moved: the seat count, the status, or the waitlist.
What a flat run means, and where a line starts
Flat between dots means it did not drift, it held and then jumped, and a line starts when dibs first saw that lecture rather than reaching back before it existed. A lecture that has never moved draws a flat line across the whole window, and one with two or three readings draws a line joining them, which is too few to read a trend from.
Lec 1 · Rudas, A. and Lee, S.A. · 8 enrolled
Filled by 8 over about 1 month
Lec 2 · Ernst, J. and Efrat, L. · 11 enrolled
Filled by 6 over about 1 month
Lec 3 · Rudas, A. and Lee, S.A. · 15 enrolled
Filled by 15 over about 1 month
How readings and alerts work
A reading and an hourly record are different things, and most charts here hold more of the second missing than present. dibs has taken readings of a section since long before it began keeping an hour-by-hour log of when it looked, so the empty stretches are dibs saying it was not keeping that log yet, not that it looked and found nothing. That is the age of the record and not a fault.
Seat counts show the last successful read, not live availability. Refreshes can be delayed by request limits or upstream interruptions. Watched sections receive priority, but an hourly update for every section is not guaranteed.
The registrar can change a seat count between our checks. Alerts depend on dibs detecting an opening and completing delivery; a quiet watch does not prove that no seat opened. Check the registrar before enrolling.