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Internet of Things for Healthcare Technologies Chinmay Chakraborty

Name: Internet of Things for Healthcare Technologies Chinmay Chakraborty
SKU: EB-22477602
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Internet of Things for Healthcare Technologies Chinmay Chakraborty Digital Instant Download

Author(s): Chinmay Chakraborty, Amit Banerjee, Maheshkumar H. Kolekar, Lalit Garg, Basabi Chakraborty

ISBN(s): 9789811541117, 9789811541124, 9811541116, 9811541124

Edition: 1st ed.

File Details: PDF, 9.68 MB

Year: 2021

Language: English

SKU: EB-22477602 Category: Engineering - Social & Cultural Aspects of Technology Tags: 9789811541117, 9811541116, Amit Banerjee, Basabi Chakraborty, Chinmay Chakraborty, Lalit Garg, Maheshkumar H. Kolekar, Things for Healthcare

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Product details:

ISBN-10 : 9811541116
ISBN-13 : 9789811541117
Author : Chinmay Chakraborty, Amit Banerjee, & 3 more

This book focuses on recent advances in the Internet of Things (IoT) in biomedical and healthcare technologies, presenting theoretical, methodological, well-established, and validated empirical work in these fields. Artificial intelligence and IoT are set to revolutionize all industries, but perhaps none so much as health care. Both biomedicine and machine learning applications are capable of analyzing data stored in national health databases in order to identify potential health problems, complications and effective protocols, and a range of wearable devices for biomedical and healthcare applications far beyond tracking individuals’ steps each day has emerged. These prosthetic technologies have made significant strides in recent decades with the advances in materials and development. As a result, more flexible, more mobile chip-enabled prosthetics or other robotic devices are on the horizon. For example, IoT-enabled wireless ECG sensors that reduce healthcare cost, and lead to betterquality of life for cardiac patient.

Table of contents:

Transmission Dynamics and Estimation of Basic Reproduction Number (R0) from Early Outbreak of Novel Coronavirus (COVID-19) in India

COVID-19 Analysis by Using Machine and Deep Learning

MML Classification Techniques for the Pathogen Based on Pnuemonia-nCOVID-19 and the Detection of Closely Related Lung Diseases Using Efficacious Learning Algorithms

Diagnosing COVID-19 Lung Inflammation Using Machine Learning Algorithms: A Comparative Study

Factors Affecting the Success of Internet of Things for Enhancing Quality and Efficiency Implementation in Hospitals Sector in Jordan During the Crises of Covid-19

IoMT-Based Smart Diagnostic/Therapeutic Kit for Pandemic Patients

The Prediction Analysis of COVID-19 Cases Using ARIMA and KALMAN Filter Models: A Case of Comparative Study

Exploration of Cough Recognition Technologies Grounded on Sensors and Artificial Intelligence

Clinical Deep Dive and Role of Ai/Ml Techniques in Tackling COVID-19

A Review on Use of Data Science for Visualization and Prediction of the COVID-19 Pandemic and Early Diagnosis of COVID-19 Using Machine Learning Models

Fuzzy Cellular Automata Model for Discrete Dynamical System Re

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