# Ai For Biomedical Applications

## BMED-4490

Introduction of artificial neural networks, rule/case-based reasoning, Bayesian methods, fuzzy-logic, genetic and evolutionary optimization techniques, and agents. The course presents the evolution of artificial neural networks from its inception to the principles of deep learning, introduces rule/case-based reasoning, fuzzy-logic, genetic algorithms and particle swarm optimization methods. Besides covering the foundation of associated methods, the course emphasizes biomedical applications and presents associated results from studies to autism, discriminating cancer types, burn severity and tissue engineering problems.

3 credits
Cross-listed with:
BMED-6490 Ai For Biomedical Applications
Prereqs:
MATH-2010 Multivar Calc & Matrix Algebra
and
MATH-2400 Intro Diff Equations

# Past Term Data
Offered
Not Offered
Offered as Cross-Listing Only
No Term Data
Simple View
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| Spring | Summer | Fall
--- | --- | --- | ---
| (Session 1) | (Session 2) |

2026

Ai For Biomedical Applications (3c)

- Uwe Kruger

Seats Taken: 7/35

2025

Ai For Biomedical Applications (3c)

- Uwe Kruger

Seats Taken: 12/35

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2001

Sensors And Instruments (4c)

- Lee E Ostrander

Seats Taken: 15/30

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