Artificial Intelligence and Machine Learning for Women’s Health Issues
- 1 Edición - 26 de abril de 2024
- Última edición
- Editores: Meenu Gupta, D. Jude Hemanth
- Idioma: Inglés
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… Leer más
Descripción
Descripción
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.
Puntos claves
Puntos claves
- 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
De interès para
De interès para
Researchers and graduate students in the areas of robotics, biomedical engineering, machine learning, and healthcare research.
Índice
Índice
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
Detalles del producto
Detalles del producto
- Edición: 1
- Última edición
- Publicado: 26 de abril de 2024
- Idioma: Inglés
Sobre los editores
Sobre los editores
MG
Meenu Gupta
Dr. Meenu Gupta is a Professor in the Department of Computer Science and Engineering, University Centre for Research and Development, Chandigarh University, Punjab, India. She is Head of Conferences and Research Outreach (Engineering Cluster) and a member of the academic leadership team at UIE–CSE. Dr. Gupta completed her Ph.D. in Computer Science and Engineering at Ansal University, Gurgaon, in 2020. She has also been a Postdoctoral Fellow at the MIR Lab in the USA. Her research interests include Machine Learning, Intelligent Systems, Data Mining, Artificial Intelligence, Image Processing, Smart Cities, Data Analysis, and Brain–Machine Interaction (BMI). She has served as a reviewer for multiple peer-reviewed journals. Dr. Gupta is a Senior Member of IEEE and a Life Member of ISTE and IAENG. She has held roles within IEEE, including positions in the IEEE Delhi Section and as an officer connected with the IEEE Robotics and Automation Society (RAS) Delhi Section.
Afiliaciones y experiencia
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.
Afiliaciones y experiencia
Professor, ECE Department, Karunya Institute of Technology and Sciences, Coimbatore, IndiaVer libro en ScienceDirect
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