Frontmatter

Chapters in this book

1. Frontmatter I
2. Contents V
3. List of Contributing Authors VII
4. 1 Introduction: fundamentals of drug discovery, telemedicine, artificial intelligence, computer vision, and IoT 1
5. 2 Machine learning transformations in drug discovery: a paradigm shift in development strategies 11
6. 3 Explainable AI approaches in drug classification from biomarkers of epileptic seizure 27
7. 4 Harnessing predictive analytics and machine learning in personalized medicine: patient outcomes and public health strategies 41
8. 5 A data-driven framework for future healthcare diagnosis through predictive analytics 59
9. 6 Revolutionizing home healthcare: telemedicine, predictive analytics, and AI-driven drug discovery 71
10. 7 AI-driven insights: a machine learning approach to lung cancer diagnosis 91
11. 8 Efficient gene selection for breast cancer classification using Brownian Motion Search Algorithm and Support Vector Machine 109
12. 9 A hybrid feature gene selection approach by integrating variance filter, extremely randomized tree, and Cuckoo Search algorithm for cancer classification 127
13. 10 HySleep_Net: a hybrid deep learning model for automatic sleep stage detection from polysomnographic signals 151
14. 11 Ambulance booking and tracking website 183
15. 12 Entropy based emergency rescue location selection with uncertain travel time 207
16. 13 Performance comparison of different deep learning ensemble models for sentiment classification of movie reviews 225
17. 14 Elevating standards in homoeopathic medicine: chemometric standardization of medicinal plant for quality assurance 253
18. 15 Evaluation of genetic diversity in Rauvolfia species using Random Amplification of Polymorphic DNA (RAPD) technique 259
19. Index