Machine Learning in Healthcare: Advances and Future Prospects [Hardcover]

1. Machine Learning Algorithms in Disease Diagnosis and Management 2. Machine Learning-Based Diagnosis and Treatment of Cancer 3. Machine Learning-Based Detection and Management of Cardiovascular Diseases 4. Monitoring the Health Status of Thyroid Patients Using Machine Learning 5. Machine Learning-Based Wearable Devices for Healthcare Applications 6. Prediction of Diabetes Using Machine Learning 7. Mental Health Index Management Using Machine Learning 8. Machine Learning Approaches for Electronic Health Record Phenotyping

Explores the complex relationship between data science and medical science, highlighting the significant impact of machine learning algorithms in multiple areas of healthcare. Discusses topics such as wearable devices and mental health management through the use of machine learning technology.

Bridge[s] the gap between data science and medical practice, focusing on disease detection, personalized therapy, and holistic patient care. The book's visionary curation underscores the transformative potential of machine intelligence in shaping the future of healthcare delivery. From the Foreword by Dhruv Galgotia, CEOm Galgotias University, Greater Noida, India

This new volume explores the integration of machine learning in healthcare, which has transformed technology for disease diagnosis, treatment, and management. The book shows the enormous possibilities made possible by computational technologies, ranging from analyzing electronic health information to predicting, detecting, and treating cancer, cardiovascular disease, thyroid disorders, and diabetes. The exploration extends beyond conventional domains, discussing topics such as wearable devices and mental health management through the use of machine learning technology.

Rishabha Malviya, PhD, is an Associate Professor of Pharmacy in the School of Medical and Allied ScienlÃ"