Spring 2027

Surgical Oncology

Small animal surgical oncology course focusing on diagnosis, treatment, and case management under veterinary supervision, emphasizing clinical reasoning and decision-making.

offering recorded1–2 credits
Recorded instructors · Spring 2027 Megan Mickelson

Summary

What you’ll be able to do

  • Develop prioritized differential diagnoses based on patient history, comprehensive physical exam, and refined problem list.

  • Develop effective strategies for diagnosing and staging solid tumors in dogs and cats.

  • Identify and select differing levels of surgical dose based on the Enneking classification scheme.

  • Articulate the role of surgery within multimodal cancer care and plan surgical management as part of an integrated approach.

  • Manage perioperative care for patients undergoing surgery.

  • Adapt client communication for gaining client trust and understanding for verbal communication and in written discharge communications.

Source: UW Guide

Grade history

↗
average GPA
letter grades

No recorded grade history.

All recorded terms · compare terms & instructors

Prerequisites

Course map

Declared in Doctor of Veterinary Medicine

  • Declared in Doctor of Veterinary Medicine
SURGSCI 715

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree
  • Declared in Doctor of Veterinary Medicine

Professors

Spring 2027
Historical instructors & teaching patterns

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
FLD 001Classroom Instruction0 / 500

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records

Student experience

the class

Provides an opportunity to participate in the diagnosis and treatment of diseases and conditions encountered in small animal surgical oncology, including management of individual cases under the direct supervision of a veterinarian. Emphasizing clinical reasoning and decision-making skills.

difficulty & workload

No workload feedback recorded.

Topics

  • Diagnosis and treatment of small animal surgical oncology diseases.
  • Diagnosis and staging of solid tumors in dogs and cats.
  • Surgical dosing levels based on the Enneking classification scheme.
  • Role of surgery in multimodal cancer care.
  • Perioperative care management.
  • Clinical reasoning and decision-making skills.

Skills

  • Developing prioritized differential diagnoses using patient history, physical exams, and problem lists.
  • Diagnosing and staging solid tumors in dogs and cats.
  • Selecting surgical doses based on the Enneking classification scheme.
  • Planning surgical management as part of integrated multimodal cancer care.
  • Managing perioperative care for surgical patients.
  • Adapting verbal and written client communication to gain trust and understanding.

Grades

Instructor

Grade distribution · % of letter grades

No grades available yet.

More grade details Grade mix, volume & source data

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
SURGSCI 715 · Spring 2027

Surgical Oncology

Recorded 2026-10-14
Raw records
[
  {
    "run_id": "20261014T203208-0851c9a1",
    "semester": "1274",
    "observed_at": "2026-10-14 17:50:09.728220+00:00",
    "offering_id": "1274:938:027277",
    "course_id": "SURGSCI 715",
    "course_uid": "course_b3de545588f945a1301e36e2",
    "term_id": "1274",
    "source_course_id": "027277",
    "source_subject_id": "938",
    "title": "Surgical Oncology",
    "credits_min": 1,
    "credits_max": 2,
    "typically_offered": "Not Applicable"
  }
]
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Madgrades

Grade history

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Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Model & dataset provenance
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "e1f9ca961114de79d32ce68c0e1b4b973e4be83782fc40258859fcf64033b2b1",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}