Combating Women's Health Issues with Machine Learning: Challenges and Solutions (Biomedical and Robotics Healthcare)

★★★★★ 4.2 123 reviews

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Management number 233436367 Release Date 2026/06/27 List Price $24.48 Model Number 233436367
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The main focus of this book is the examination of women’s health issues and the role machine learning can play as a solution to these challenges. This book will illustrate advanced, innovative techniques/frameworks/concepts/machine learning methodologies, enhancing the future healthcare system. Combating Women’s Health Issues with Machine Learning: Challenges and Solutions examines the fundamental concepts and analysis of machine learning algorithms. The editors and authors of this book examine new approaches for different age-related medical issues that women face. Topics range from diagnosing diseases such as breast and ovarian cancer to using deep learning in prenatal ultrasound diagnosis. The authors also examine the best machine learning classifier for constructing the most accurate predictive model for women’s infertility risk. Among the topics discussed are gender differences in type 2 diabetes care and its management as it relates to gender using artificial intelligence. The book also discusses advanced techniques for evaluating and managing cardiovascular disease symptoms, which are more common in women but often overlooked or misdiagnosed by many healthcare providers.The book concludes by presenting future considerations and challenges in the field of women’s health using artificial intelligence. This book is intended for medical researchers, healthcare technicians, scientists, programmers and graduate-level students looking to understand better and develop applications of machine learning/deep learning in healthcare scenarios, especially concerning women’s health conditions. Read more

ASIN B0CKFJC1HG
XRay Not Enabled
Format Print Replica
ISBN13 978-1000964684
Edition 1st
Language English
File size 23.8 MB
Page Flip Not Enabled
Publisher CRC Press
Word Wise Not Enabled
Accessibility Learn more
Publication date October 23, 2023
Enhanced typesetting Not Enabled

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