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. It will illustrate advanced, innovative techniques/frameworks/concepts/machine learning methodologies, enhancing the future healthcare system. Combating Female Health Issues with Machine Learning: Challenges and Solutions examines machine learning algorithms' fundamental concepts and analysis.
The editors and authors of this book examine new approaches for different medical issues women face as they relate to age. 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 ML/DL in healthcare scenarios, especially concerning women's health conditions.
About the Author: Dr. Meenu Gupta is an Associate Professor at the UIE-CSE Department, Chandigarh University, India. She completed her Ph.D. in Computer Science and Engineering with an emphasis on Traffic Accident Severity Problems from Ansal University, Gurgaon, India, in 2020. She has more than 14 years of teaching experience. Her research areas cover Machine Learning, Intelligent Systems, and Data mining, with a specific interest in Artificial Intelligence, Image Processing and Analysis, Smart Cities, Data Analysis, and Human/Brain-machine Interaction (BMI). She has edited five books and authored four engineering books. She reviews several journals, including Big Data, CMC, Scientific Reports, and TSP. She is a life member of ISTE and IAENG. She has authored or co-authored more than 30 book chapters and over 80 papers in refereed international journals and conferences.
Dr. D. Jude Hemanth is an Associate Professor in the Department of ECE at Karunya University, Coimbatore, India. He also holds the "Visiting Professor" position in the Faculty of Electrical Engineering and Information Technology at the University of Oradea, Romania. Dr. D. Jude Hemanth received his BE degree in ECE from Bharathiar University, Coimbatore, Tamil Nadu, India, in 2002, his ME degree in communication systems from Anna University, Tamil Nadu, India, in 2006, and his Ph.D. from Karunya University, Coimbatore, India, in 2013. His research areas include Computational Intelligence and Image processing, Communication Systems, Biomedical Engineering, Robotics and Healthcare, Computational Intelligence and Information Systems, and Artificial Intelligence. Jude Hemanth is an editor of the Neuroscience Informatics Journal.
