Fall 2026

Introduction to Energy-tissue Interactions

Introduction to energy-tissue interactions focusing on therapeutic medical applications of thermal, electromagnetic, and acoustic energies.

no offering record for this termCredits unavailable
Recorded instructors · Fall 2026 No instructors listed

Summary

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Recent recorded grades — Fall 2022: 3.50 GPA, 81.8% A/AB (n=11 letter grades); Fall 2023: 3.50 GPA, 84.6% A/AB (n=13 letter grades); Spring 2025: 3.79 GPA, 92.9% A/AB (n=14 letter grades).

Grade history

average GPA
letter grades
A
AB
B
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Prerequisites

Course map

PHYSICS 202, 208, 248, or PHYSICS/​MED PHYS 265, or graduate/professional standing

BME/MEDPHYS 535

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Prerequisite text tree

Professors

Fall 2026

No instructors recorded for this selection.

Historical instructors & teaching patterns

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Calendar & sections

Fall 2026

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Meeting source records

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Student experience

the class

Recent recorded grades — Fall 2022: 3.50 GPA, 81.8% A/AB (n=11 letter grades); Fall 2023: 3.50 GPA, 84.6% A/AB (n=13 letter grades); Spring 2025: 3.79 GPA, 92.9% A/AB (n=14 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Thermal, electromagnetic, and acoustic energy interactions with biological tissues.
  • Therapeutic medical applications of energy-tissue interactions.

Skills

  • Analyze physical interactions of thermal, electromagnetic, and acoustic energies with biological tissues.

Grades

Latest available · Spring 2025— not enough history to project Fall 2026.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Spring 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

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Selected offering source records

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Raw records
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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

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Model 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": "a9f2680dc0d78871b6b017b60f2c1594c3e5d317e59445d44e749daff8cf6c87",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}