Advancing Women's Health Through Data Science and Personal Health Informatics
Self-paced
1 credit
Full course description
Description
This training module explores the role of data science and personal health informatics in advancing women's health, with a focus on endometriosis. It discusses challenges in diagnosis, symptom tracking, and the impact of patient-generated data on research and treatment. The session highlights the importance of integrating clinical, epidemiological, and patient-reported data for improved healthcare outcomes.
Target Audience
This module is designed for healthcare professionals, data scientists, biomedical researchers, and policy-makers interested in the intersection of women's health, informatics, and machine learning.
Learning Outcomes
After completing this training, you will be able to:
- Explain the current challenges in diagnosing and managing endometriosis.
- Identify the role of data science and informatics in improving women's health outcomes.
- Analyze the impact of patient-generated health data on disease characterization and treatment personalization.
- Evaluate the benefits and limitations of self-tracking applications in chronic disease management.