Decision Making in Health Care
Recorded 2026-09-07 Fall 2026
Decision Making in Health Care
ISYE 517 introduces decision sciences in healthcare, teaching decision trees, sensitivity analysis, Markov processes, and Monte Carlo simulations.
Recorded instructors · Fall 2026 No instructors listed
Summary
1 / 5
One historical review notes that Alagoz did not make the course more difficult than necessary, suggesting a manageable workload.
Grade history
↗ average GPA
letter grades
letter grades
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All recorded terms · compare terms & instructors
Prerequisites
Course map(STAT/MATH 309,STAT 311, or STAT/MATH 431) and (I SY E 323 or E C E/COMP SCI/I SY E 524), or graduate/professional standing, or member of Engineering Guest Students
- take all
- take one
- graduate/professional standing
- member of Engineering Guest Students
This is a best-effort interpretation; check the catalog requirements above.
Prerequisite text tree
- Any of
- All of
- Any of
- Any of
- graduate/professional standing
- member of Engineering Guest Students
Professors
Fall 2026No instructors recorded for this selection.
Historical instructors & teaching patterns
Historical reviews of Oguzhan Alagoz: Oguzhan Alagoz is described as passionate and engaging, with reviewers noting his effort to know students by name and his use of real-world examples. Students found his lectures enjoyable and highly recommended his class, citing his enthusiasm and accessible teaching style.
OGUZHAN ALAGOZ is recorded teaching in Spring 2011, Fall 2013, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Fall 2020, Fall 2021, Fall 2022, Fall 2023, Fall 2024, Fall 2025. Recorded history may be incomplete and does not establish a future schedule.
Recorded history may be incomplete and does not establish a future schedule.
Calendar & sections
Fall 2026Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
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Times are Central. Select a meeting for details; export includes recorded dates for the selected sections.
Meeting source records
No records available.
Student experience
the class
Historical reviews for Oguzhan Alagoz describe a highly recommended, passionate instructor who connects topics to his experience and makes the class accessible.
Recent recorded grades — Fall 2023: 3.59 GPA, 81.8% A/AB (n=33 letter grades); Fall 2024: 3.64 GPA, 75.0% A/AB (n=32 letter grades); Fall 2025: 3.57 GPA, 69.0% A/AB (n=29 letter grades).
difficulty & workload
One historical review notes that Alagoz did not make the course more difficult than necessary, suggesting a manageable workload.
Historical reviews of Oguzhan Alagoz: Students appreciated Alagoz's passion, interesting examples, and effort to learn student names, finding lectures engaging and enjoyable.
Topics
Skills
Grades
Latest available · Fall 2025— not enough history to project Fall 2026.
Grade distribution · % of letter grades
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AB
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BC
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Grades over time
Through Fall 2025
More grade details Grade mix, volume & source data
Not enough comparable courses for Fall 2026 in UW–Madison.
Sources & history
UW–Madison
Catalog & offerings
Descriptions, prerequisites, and recorded course offerings.
Catalog observation history
Observations at scan time; dates do not imply when a catalog change took effect.
Selected offering source records
Raw records
[
{
"run_id": "20260907T155543-ce3781c4",
"semester": "1272",
"observed_at": "2026-09-07 15:55:43.033547+00:00",
"offering_id": "1272:490:023463",
"course_id": "ISYE 517",
"course_uid": "course_79b5e9b5db80577aeb7f07f1",
"term_id": "1272",
"source_course_id": "023463",
"source_subject_id": "490",
"title": "Decision Making in Health Care",
"credits_min": 3,
"credits_max": 3,
"typically_offered": "Fall, Spring"
}
]Rate My Professors
Student reviews
Original comments behind the course and instructor summaries.
Read original reviews
Madgrades
Grade history
Recorded grade distributions by term, section, and instructor.
Explore recorded gradesModel outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
{
"model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
"model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
"task_version": "14",
"output_id": "9fd9c077c9311a3ba1a312a8a02d2ceab6533ad005dab4586779c30ae20b72e3",
"requirements_status": "valid",
"dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
"observed_at": "2026-09-07 15:55:43.033547+00:00"
}