Biased health algorithms produce inaccurate diagnoses and unfair treatment recommendations. This course teaches how to identify bias in medical AI systems and take steps to improve accuracy and patient safety.
Objectives:
- Recognise how biased training data affects diagnostic accuracy across patients
- Identify bias patterns in symptom tracking and treatment recommendation systems
- Check data sources to ensure diverse patient populations are represented
- Review AI results for disparities in accuracy across demographic groups
- Include diverse patient inputs when designing or testing health AI systems
