Smart Healthcare and Machine Learning

• Titel: Smart Healthcare and Machine Learning
• Mitwirkende: Chaurasia, Mousmi Ajay [HerausgeberIn]
• Mitwirkende: Balaji, Prasanalakshmi [HerausgeberIn]
• Mitwirkende: Frery, Alejandro C. [HerausgeberIn]
• Verf.angabe: edited by Mousmi Ajay Chaurasia, Prasanalakshmi Balaji, Alejandro C. Frery
• Ausgabe: 1st ed. 2024.
• Verlagsort: Singapore
• Verlagsort: Singapore
• Verlag: Springer Nature Singapore
• Verlag: Imprint: Springer
• E-Jahr: 2024
• Jahr: 2024.
• Jahr: 2024.
• Umfang: 1 Online-Ressource(XIII, 337 p. 128 illus., 115 illus. in color.)
• Gesamttitel/Reihe: Advanced Technologies and Societal Change
• ISBN: 978-981-9733-12-5
• DOI: doi:10.1007/978-981-97-3312-5
• Datenträger: Online-Ressource
• Sprache: eng
• Bibliogr. Hinweis: Erscheint auch als : Druck-Ausgabe
• Bibliogr. Hinweis: Erscheint auch als : Druck-Ausgabe
• Bibliogr. Hinweis: Erscheint auch als : Druck-Ausgabe
• K10plus-PPN: 1895508916
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext

Abstract

-- Predictive Modeling for Patient Outcomes in Smart Healthcare Systems. -- Machine Learning for Personalized Treatment Recommendations. -- Smart Health Monitoring: Data Collection and Analysis with Machine Learning. -- Enhancing Medical Imaging through Dimension Reduction Learning. -- Natural Language Processing for Health Record Management. -- Machine Learning-driven Drug Discovery and Development.

Abstract

The book explores the convergence of healthcare and cutting-edge technology, making it a captivating subject for readers interested in future research. Smart healthcare with machine learning techniques offers a transformative paradigm that utilizes the power of new technology, data analytics, and interconnected devices to enhance the quality, efficiency, and accessibility of healthcare services. This involves leveraging Internet of Things (IoT) devices, wearable technology, and machine learning algorithms to monitor patient health, predict medical conditions, and offer personalized treatment recommendations. This innovative combination not only enhances diagnostics and treatment but also addresses the research challenges of healthcare access and delivery in an increasingly connected world. By exploring the synergy between smart healthcare and machine learning, the book helps to understand how these technologies can collaborate to revolutionize patient care and healthcare delivery. This book is an outcome with applications of future technologies to overcome the toughest humanitarian challenges from an engineering approach.