Artificial Intelligence and Machine Learning for Women’s Health Issues 1st Edition

Artificial Intelligence and Machine Learning for Women’s Health Issues, 1st Edition by Meenu Gupta and D. Jude Hemanth offers a timely, practical roadmap for applying AI and ML to improve women’s health across clinical, research, and public-health settings.

Start with a clear, compelling overview of how data-driven technologies are transforming diagnosis, risk prediction, and personalized care for conditions such as reproductive health, breast and gynecologic cancers, maternal health, and chronic diseases affecting women. The book balances technical rigor with clinical relevance, making complex algorithms accessible to clinicians, data scientists, students, and healthcare leaders.

Inside, readers will find case studies and applied examples demonstrating real-world impact—from image-based diagnostic tools and predictive models for prenatal risk to remote-monitoring solutions tailored for low-resource settings across India, South Asia and other global regions. Ethical considerations, bias mitigation, and regulatory implications are addressed to ensure solutions are safe, equitable, and culturally sensitive.

This edition is ideal for professionals seeking actionable insights: learn how to design interpretable models, integrate ML into clinical workflows, and scale interventions that improve outcomes for diverse female populations. Practical frameworks help teams translate research into measurable health gains.

For anyone invested in the future of women’s healthcare—clinicians, public-health policymakers, AI practitioners, and academic researchers—this title is an essential reference. Discover strategies that bridge technology and compassionate care. Order your copy today to lead the next wave of innovation in women’s health.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.