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Transforming Gender-Based Healthcare with AI and Machine Learning

Edited by Meenu Gupta, Edited by Rakesh Kumar, Edited by Zhongyu Lu

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This book provides a thorough exploration of the intersection between gender-based healthcare disparities and the transformative potential of artificial intelligence (AI) and machine learning (ML). It covers a wide range of topics from fundamental concepts to practical applications. Transforming Gender-Based Healthcare with AI and Machine Learning incorporates real-world case studies and success stories to illustrate how AI and ML are actively reshaping gender-based healthcare and offers examples that showcase tangible outcomes and the impact of technology in healthcare settings. The book delves into the ethical considerations surrounding the use of AI and ML in healthcare and addresses issues related to privacy, bias, and responsible technology implementation. Empasis is placed on patient-centered care, and the book discusses how technology empowers individuals to actively participate in their healthcare decisions and promotes a more engaged and informed patient population. Written to encourage interdisciplinary collaboration and highlight the importance of cooperation between health professionals, technologies, researchers, and policymakers, this book portrays how this collaborative approach is essential for achieving transformative goals and is not only for professionals but can also be used at the student level as well.

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