Artificial Intelligence and Machine Learning for Women’s Health Issues
- 1st Edition - April 30, 2024
- Editors: Meenu Gupta, D. Jude Hemanth
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 2 1 8 8 9 - 7
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 2 1 8 9 0 - 3
Artificial Intelligence and Machine Learning for Women’s Health Issues discusses the applications, challenges, and solutions that machine learning can bring to women’s heal… Read more
Artificial Intelligence and Machine Learning for Women’s Health Issues discusses the applications, challenges, and solutions that machine learning can bring to women’s health challenges. The book illustrates advanced, innovative techniques, frameworks, concepts, and methodologies of machine learning which enhance the future healthcare system. This book's primary focus is on women’s health issues and machine learning's role in providing solutions to these challenges, providing novel ideas for feasible implementation. It also provides an early-stage analysis for early diagnosis of women’s health issues.
- Provides fundamental concepts and analysis of machine learning algorithms used to aid in the diagnosis of women’s health issues
- Guides researchers to specific ideas, tools, and practices most applicable to product/service development, innovation problems, and opportunities
- Provides hands-on chapters that describe frameworks, applications, best practices, and case studies of future directions of applied machine learning in women’s healthcare
Researchers and graduate students in the areas of robotics, biomedical engineering, machine learning, and healthcare research.
1. Role of Artificial Intelligence in Gynecology and Obstetrics
Chander Prabha and Meena Malik
2. Prediction of Female Pregnancy Complication using Artificial Intelligence
Charvi .
3. Early Stage Prediction of Endometriosis Cancer Using Fuzzy Machine Learning Technique
vijay kumar and Kiran Pal
4. Artificial Intelligence approaches for ultrasound examination in pregnancy
Somya Srivastava
5. Early assessment of pregnancy using machine learning
Chander Prabha and Dr. Meenu Gupta
6. Ensemble learning-based analysis of perinatal health disorders in women
Malvika Gupta, Puneet Garg and Chetan Malik
7. Machine learning applications to predict gestational diabetes in early pregnancy
Poonam Joshi
8. Contribution of artificial intelligence to improve women health in pregnancy
Gulafshan Mirza, Poonam Joshi, Sapna Rawat, Haidar Saddu and Yashika Uniyal
9. Artificial Intelligence based Prediction of Health Risks Among Women during Menopause
Medha Malik
10. Mammography Screening of Women in Forties: Benefits and Risks
Jyotsana Suyal
11. Machine learning approach to predict the early assessment of Post partum depression
Srishti Morris and Dipika Rawat
12. Artificial intelligence approaches for polycystic ovarian syndrome
Mehvish Mohiuddin Bhat
13. Improving women's mental health through AI-powered interventions and diagnoses
Rahul Negi
14. Early stage breast cancer diagnostics using Vision Transformers
Naveen Venkatesh S, Sugumaran V and Divya S
15. Recent and Future Applications of Artificial Intelligence in Obstetric Ultrasound Examination
Shalu Verma, Alka Singh, Kiran Dobhal, Nidhi Gairola and Vikash Jakhmola
16. Deadly Canker of Cervix Tackled With Early Diagnosis using Machine Learning
Selvarathi M, Priya Rajasekaran, Kunnathur Murugesan Sakthivel, Baskar M and Jude Immaculate H
17. AI, Women’s health care and Trust: Problems and Prospects
Vaishali Singh
18. Role of Artificial Intelligence and Machine learning in women's health: Challenges and Solutions
Sapna Rawat
Chander Prabha and Meena Malik
2. Prediction of Female Pregnancy Complication using Artificial Intelligence
Charvi .
3. Early Stage Prediction of Endometriosis Cancer Using Fuzzy Machine Learning Technique
vijay kumar and Kiran Pal
4. Artificial Intelligence approaches for ultrasound examination in pregnancy
Somya Srivastava
5. Early assessment of pregnancy using machine learning
Chander Prabha and Dr. Meenu Gupta
6. Ensemble learning-based analysis of perinatal health disorders in women
Malvika Gupta, Puneet Garg and Chetan Malik
7. Machine learning applications to predict gestational diabetes in early pregnancy
Poonam Joshi
8. Contribution of artificial intelligence to improve women health in pregnancy
Gulafshan Mirza, Poonam Joshi, Sapna Rawat, Haidar Saddu and Yashika Uniyal
9. Artificial Intelligence based Prediction of Health Risks Among Women during Menopause
Medha Malik
10. Mammography Screening of Women in Forties: Benefits and Risks
Jyotsana Suyal
11. Machine learning approach to predict the early assessment of Post partum depression
Srishti Morris and Dipika Rawat
12. Artificial intelligence approaches for polycystic ovarian syndrome
Mehvish Mohiuddin Bhat
13. Improving women's mental health through AI-powered interventions and diagnoses
Rahul Negi
14. Early stage breast cancer diagnostics using Vision Transformers
Naveen Venkatesh S, Sugumaran V and Divya S
15. Recent and Future Applications of Artificial Intelligence in Obstetric Ultrasound Examination
Shalu Verma, Alka Singh, Kiran Dobhal, Nidhi Gairola and Vikash Jakhmola
16. Deadly Canker of Cervix Tackled With Early Diagnosis using Machine Learning
Selvarathi M, Priya Rajasekaran, Kunnathur Murugesan Sakthivel, Baskar M and Jude Immaculate H
17. AI, Women’s health care and Trust: Problems and Prospects
Vaishali Singh
18. Role of Artificial Intelligence and Machine learning in women's health: Challenges and Solutions
Sapna Rawat
- Edition: 1
- Published: April 30, 2024
- Language: English
MG
Meenu Gupta
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 15 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 five edited and four authored books. She has also authored or co-authored more than 20 book chapters and over 80 papers in refereed international journals and conferences. She has five filled patents and was awarded the best faculty and department researcher in 2021 and 2022.
Affiliations and expertise
Associate Professor, Department of Computer Science and Engineering University Centre of Research and Development Chandigarh University, Punjab, IndiaDH
D. Jude Hemanth
Dr. D. Jude Hemanth is currently working as a professor in Department of ECE, Karunya University, Coimbatore, India. He also holds the position of “Visiting Professor” in Faculty of Electrical Engineering and Information Technology, University of Oradea, Romania. He also serves as the “Research Scientist” of Computational Intelligence and Information Systems (CI2S) Lab, Argentina; LAPISCO research lab, Brazil; RIADI Lab, Tunisia; Research Centre for Applied Intelligence, University of Craiova, Romania and e-health and telemedicine group, University of Valladolid, Spain.
Dr. Hemanth received his B.E degree in ECE from Bharathiar University in 2002, M.E degree in communication systems from Anna University in 2006 and Ph.D. from Karunya University in 2013. He has published 37 edited books with reputed publishers such as Elsevier, Springer and IET. His research areas include Computational Intelligence and Image processing. He has authored more than 200 research papers in reputed SCIE indexed International Journals and Scopus indexed International Conferences.
Affiliations and expertise
Professor, ECE Department, Karunya Institute of Technology and Sciences, Coimbatore, IndiaRead Artificial Intelligence and Machine Learning for Women’s Health Issues on ScienceDirect