Objective:

To explore how artificial intelligence (AI) can address disparities in women's health, such as underdiagnosis and misdiagnosis, by uncovering patterns in data that have historically been overlooked.

Approach:

Key Findings:

• Women spend 25% more of their lives in poor health compared to men, highlighting a significant health disparity.
• AI can help identify sex-specific biomarkers and improve risk stratification, potentially leading to more effective treatments.
• AI-enabled analysis can shorten the diagnostic process for conditions like endometriosis, which often takes years to diagnose.

Interpretation:

AI has the potential to enhance personalized care in women's health by addressing both intergroup and intragroup differences, ultimately leading to better health outcomes.

Limitations:

• Algorithms trained on nonrepresentative data may reinforce disparities, particularly in underrepresented populations.
• Privacy concerns exist with the use of wearable devices and menstrual trackers, which may expose sensitive health data.

Conclusion:

AI can significantly contribute to understanding and improving women's health, provided that ethical considerations and inclusive data practices are prioritized to ensure equitable health outcomes.

Sources:

• JAMA Internal Medicine
Attribution Notice

This content is an AI-generated, fully rewritten summary based on a published scholarly article. It does not reproduce the original text and is not a substitute for the original publication. Readers are encouraged to consult the source for full context, data, and methodology.