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chaurasia m smart healthcare machine learning 2024

Type:: E-books
Files:: 2
Size:: 7.9 MB
Uploaded On:: July 24, 2024, 10:35 a.m.
Added By:: andryold1
Seeders:: 3
Leechers:: 7
Info Hash:: 02E6036CF145D867A02830EC2048ECB167F9B6F2

Textbook in PDF format 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. About This Book Big Data Analytics for Big Medical Data—Tools Applications and Challenges AB-BiL: A Deep Learning Model to Analyze Depression Detection in Imbalanced Data Synchronization Analysis of Complex-Valued Artificial Neural Networks with Distributed Delays in Medical Image Processing Deep Q-Learning-Based Neural Network for Secure Data Transmission in Internet of Things (IoT) Healthcare Application Integrating Artificial Intelligence for Enhanced Tuberculosis Diagnosis and Management: A Comprehensive Analysis An Effective Cost-Sensitive Learning Approach for Detection of COVID-19 with Lung Diseases IoT in Healthcare: Applications, Benefits, Challenges, and Real-Time Use Cases An ML Approach to Analyze Cyberthreats and Vulnerabilities in the Healthcare Ecosystem Reliable and Efficient Healthcare System Using Artificial Intelligence Advancing Precision Medicine: An Exploration of Hybrid Deep Learning Approaches for Automated Human Brain Tissue Segmentation and Tumour Localization in MRI O-RAN in Private Network for Digital Health Applications Using Twofish Encryption in the Internet of Things Mobile Nets: Prediction of Black Fungus Disease Through Image Classification A Secured IoT Healthcare Architecture-Based Access Control System Using Deep Learning IoT Paradigm for Healthcare System to Secure the Patients Real-Time Data Application of the Internet of Things in the Healthcare Field A Predictive Diagnostic Model for Diabetes Using Machine Learning Technique A Novel Development of Medical Technology and AI for Intelligent Healthcare A Blockchain-Based Hybrid SVMLR Approach for IoT-Healthcare Non-Shannon Perspective on the IFS’s Anomalous Viable One-To-One Communication Signal Detection Pattern with Discrete Weighted Distribution Digital Imaging and Communication in Medicine (DICOM): Biomedical and Health Informatics: Imaging and Interoperability Using HL7 and DICOM Algorithms with Physics Inspiration Used in Biomedical Imaging for a Better Future

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chaurasia m smart healthcare machine learning 2024

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