Machine Learning and Artificial Intelligence in Healthcare Systems - Shaikh, Tawseef Ayoub; Hakak, Saqib; Rasool, Tabasum;(szerk.) - Prospero Internetes Könyváruház
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Machine Learning and Artificial Intelligence in Healthcare Systems

Tools and Techniques
 
Kiadás sorszáma: 1
Kiadó: CRC Press
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30 675 Ft (29 215 Ft + 5% áfa)
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A kedvezmény érvényes eddig: 2024. december 31.
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Rövid leírás:

This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine by combining design and problem-solving skills of engineering with health sciences to advance healthcare treatment.

Hosszú leírás:

This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine by combining design and problem-solving skills of engineering with health sciences to advance healthcare treatment.


Machine Learning and Artificial Intelligence in Healthcare Systems: Tools and Techniques discusses AI-based smart paradigms for reliable prediction of infectious disease dynamics; such paradigms can help prevent disease transmission. It highlights the different aspects of using extended reality for diverse healthcare applications and aggregates the current state of research. The book offers intelligent models of the smart recommender system for personal well-being services and computer-aided drug discovery and design methods. Case studies illustrating the business processes that underlie the use of big data and health analytics to improve healthcare delivery are center stage. Innovative techniques used for extracting user social behavior (known as sentiment analysis for healthcare-related purposes) round out the diverse array of topics this reference book covers.


Contributions from experts in the field, this book is useful to healthcare professionals, researchers, and students of industrial engineering, systems engineering, biomedical, computer science, electronics, and communications engineering.

Tartalomjegyzék:
1. Artificial Intelligence Challenges, Principles, and Applications in Smart Healthcare Systems.  2. Systematic View and Impact of Artificial Intelligence in Smart Healthcare Systems, principles, challenges and Applications.  3. Application of Machine Learning Techniques in COVID-19 Epidemiology: A Glimpse.  4. Automated Seven-Level Skin Cancer Staging Diagnosis in Dermoscopic images using Deep Learning.  5. Ensemble Classifier Based Predictive Model for Type-2 Diabetes Mellitus Prediction.  6. Machine Learning Approaches for Analysis in Smart Healthcare Informatics.  7. Smart Approaches for Diagnosis of Brain Disorders using Artificial Intelligence.  8. Bridging the Gap Between Technology and Medicine: Approaches of Artificial Intelligence in Healthcare.  9. Brain Tumor Classification using Transfer Learning.  10. Advanced Bayesian Estimation Of Weibull In Early Stage Eye Loss Prediction In Diabetic Retinopathy.  11. Automated Sleep Staging Using Single-Channel EEG SIgnal based on Machine Learning Approaches.  12. Machine Learning Based Intelligent Assistant for Smart Healthcare.  13. AI-Enabled Sentiment Analysis on COVID-19 Vaccination: A Twitter based study.  14. An Early Diagnosis of Lung Nodule Using CT Images based on Hybrid Machine Learning techniques.  15. Early Detection of Alzheimer?s Disease Assisted by AI-Powered Human-Robot Communication.