Selected for competitive scholarship to participate in the Health AI Bias Datathon, focused on identifying and mitigating algorithmic bias in healthcare AI systems.
Program Focus
- Analyzing bias in clinical decision support systems
- Developing fairness metrics for healthcare ML models
- Creating bias mitigation strategies for medical AI
- Collaborative research with healthcare professionals
Skills Developed
- Healthcare data analysis and HIPAA compliance
- Fairness-aware machine learning techniques
- Statistical methods for bias detection
- Interdisciplinary collaboration in health informatics
Impact
Contributed to research on ensuring equitable AI outcomes across diverse patient populations.