Artificial Intelligence and Machine Learning for Women's Health Issues

Erscheinungsjahr 2024
ISBN: 978-0-443-21889-7
Verlag: Elsevier Inc

Buch, Englisch, 290 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 392 g

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.

Autoren/Hrsg.

Gupta, Meenu

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Gynäkologie, Geburtshilfe
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik

Inhaltsverzeichnis

1. Role of Artificial Intelligence in Gynecology and Obstetrics
2. Prediction of Female Pregnancy Complication using Artificial Intelligence
3. Early Stage Prediction of Endometriosis Cancer Using Fuzzy Machine Learning Technique
4. Artificial Intelligence approaches for ultrasound examination in pregnancy
5. Early assessment of pregnancy using machine learning
6. Ensemble learning-based analysis of perinatal health disorders in women
7. Machine learning applications to predict gestational diabetes in early pregnancy
8. Contribution of artificial intelligence to improve women health in pregnancy
9. Artificial Intelligence based Prediction of Health Risks Among Women during Menopause
10. Mammography Screening of Women in Forties: Benefits and Risks
11. Machine learning approach to predict the early assessment of Post partum depression
12. Artificial intelligence approaches for polycystic ovarian syndrome
13. Improving women's mental health through AI-powered interventions and diagnoses
14. Early stage breast cancer diagnostics using Vision Transformers
15. Recent and Future Applications of Artificial Intelligence in Obstetric Ultrasound Examination
16. Deadly Canker of Cervix Tackled With Early Diagnosis using Machine Learning
17. AI, Women’s health care and Trust: Problems and Prospects
18. Role of Artificial Intelligence and Machine learning in women's health: Challenges and Solutions

Über Autor(innen)

Gupta, Meenu
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.