Combating Women's Health Issues with Machine Learning

Combating Women's Health Issues with Machine Learning

Challenges and Solutions

Hemanth, D.; Gupta, Meenu

Taylor & Francis Ltd

04/2025

238

Mole

9781032457529

Pré-lançamento - envio 15 a 20 dias após a sua edição

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1. Role of Machine Learning in Women's Health: A Review Analysis. 2. Predicting Anxiety, Depression and Stress in Women Using Machine Learning Algorithms. 3. Gender-based Analysis of the Impact of Cardiovascular Disease Using Machine Learning: A Comparative Analysis. 4. Lifestyle and Dietary Management Associated With Chronic Diseases in Women Using Deep Learning. 5. Gender Differences in Diabetes Care and Management using AI. 6. Prenatal Ultrasound Diagnosis Using Deep Learning Approaches. 7. Deep Convolutional Neural Network for the Prediction of Ovarian Cancer. 8. Risk Prediction and Diagnosis of Breast Cancer using ML Algorithms. 9. Comparative Analysis of Machine Learning Algorithms to Diagnose Polycystic Ovary Syndrome. 10. A Comparative Analysis of Machine Learning Approaches in Endometrial Cancer. 11. Machine Learning Algorithm-Based Early Prediction of Diabetes: A New Feature Selection Using Correlation Matrix with Heat Map. 12. Analyzing Factors for Improving Pregnancy Outcomes Using Machine Learning. 13. Future Consideration and Challenges in Women's Health Using AI.
Machine Learning;Healthcare;Alzheimer's disease;Cancer;HIV;PCOS;MR Images;Anxiety;Deep Learning;Heart Disease;Dataset;MLA;RF;SVM;Ml Model;F1 Score;Ml Technique;CNN Model;T2 Dm;Roc Curve;PCOS Condition;Convolutional Layer;Ann Model;Breast Cancer;Extreme Learning Machines;RGB;HE4 Level;DBT;EC Diagnosis;EC Patient;Breast Cancer Related Lymphedema;Parallel Random Access Machines;High AUC