Buy Applied Artificial Intelligence A Biomedical Perspective | Scientific Books, New Arrivals, FOREIGN BOOKS , A Social Legal Perspective

ABOUT THE BOOK

This book explores the advancements and future challenges in biomedical application developments using breakthrough technologies like Artificial Intelligence (AI), Internet of Things (IoT), and Signal Processing. It will also contribute to biosensors and secure systems,and related research. Applied Artificial Intelligence: A Biomedical Perspective begins by detailing recent trends and challenges of applied artificial intelligence in biomedical systems.

Part I of the book presents the technological background of the book in terms of applied artificial intelligence in the biomedical domain. Part II demonstrates the recent advancements in automated medical image analysis that have opened ample research opportunities in the applications of deep learning to different diseases. Part III focuses on the use of cyberphysical systems that facilitates computing anywhere by using medical IoT and biosensors and the numerous applications of this technology in the healthcare domain. Part IV describes the different signal processing applications in the healthcare domain. It also includes the prediction of some human diseases based on the inputs in signal format. Part V highlights the scope and applications of biosensors and security aspects of biomedical images.

The book will be beneficial to the researchers, industry persons, faculty, and students working in biomedical applications of computer science and electronics engineering. It will also be a useful resource for teaching courses like AI/ML, medical IoT, signal processing, biomedical engineering, and medical image analysis.

TABLE OF CONTENTS

PART I Applied Artificial Intelligence for Biomedical Applications

Chapter 1 Healthcare Fees-Centric to Value-Centric Transformation through Data, Analytics, and Artificial Intelligence
Sanjeev Manchanda and Mahesh Kshirsagar

Chapter 2 AI-Based Healthcare: Top Businesses and Technologies
Dipali Ghatge and K. Rajeswari

Chapter 3 Insights into AI, Machine Learning, and Deep Learning
Aditya Shinde and Swati Shinde

PART II Medical Image Processing Using Deep Learning Algorithms

Chapter 4 Deep Learning for Visual Perceptual Brain Decoding as Image Classification
Saumya Kushwaha, Priyanka Jain, and N. K. Jain

Chapter 5 Automatic Brain Tumor Segmentation in Multimodal MRI Images Using Deep Learning
Seyyed-Mahdi Banan-Khojasteh and Mohammad-Ali Balafar

Chapter 6 Automated Prediction of Lung Cancer Using Deep Learning Algorithms
S. Das, P. Kumar, S. Pal, and S. Majumder

Chapter 7 Cervical Cancer Screening Approach Using AI
D. Santhi, M. Carmel Sobia, and M. Jayalakshmi

Chapter 8 Progression Detection of Multiple Sclerosis in Brain MRI Images
Santosh Chede and Surekha Washimkar

Chapter 9 Artificial Intelligence Clustering Techniques on Dermoscopic Skin Lesion Images
V. Saravana Kumar, M. Kavitha, S. Anantha Sivaprakasam, E. R. Naganathan, Sunil Bhutada, K. G. Suma, Lakshmi Priya, and M. Kavitha

Chapter 10 Automated Alzheimer’s Disease Detection with Optimized Fuzzy Neural Network
Preeti Topannavar, Dr. D. M. Yadav, and Dr. Varsha Bendre

Chapter 11 A Comprehensive Survey with Bibliometric Analysis on Recent Research Opportunities of Multimodal Medical Image Fusion in Various Applications
Manjiri A Ranjanikar, Nilam Upasani, Asmita Manna, Jaishri M. Waghmare, Shimpy Goyal, Rachana Y. Patil, and Bharati P. Vasgi

PART III Medical IOT and Recent Trends

Chapter 12 Big Data in IoT for Healthcare Application
Nilam Upasani, Deepali Joshi, Sanika Upasani, and Swayam Pendgaonkar

Chapter 13 Automatic Detection of Diabetic Retinopathy to Avoid Blindness
Smita Das, Sushanta Das, Saptarshi Debray, Madhusudhan Mishra, and Swanirbhar Majumder

Chapter 14 A Review on Wireless BAN to Measure the Respiration Rate Using SoC Architecture
H. R. Archana, H. H. Surendra, A. P. Jyothi, S. Lalitha, and K. N. Madhusudhan

PART IV Biomedical Signal Processing

Chapter 15 Deep Feature Extraction for EEG Signal Classification in Motor Imagery Tasks
Rashmi S and Vani Ashok

Chapter 16 Effect of Age in Normal Women by Heart Rate Variability Analysis
Anjali C. Birajdar and Vijaya R. Thool

Chapter 17 EEG Signal Analysis Using Machine Learning and Artificial Intelligence for Identification of Brain Dysfunction
Rajeswari Aghoram and S. B. Athira

PART V Recent Trends in Biomedical Applications

Chapter 18 Cervical Cancer Screening Methods: Comprehensive Survey
Swati Shinde, Madhura Kalbhor, and Aditya Shinde

Chapter 19 Understanding Assessment Methods and Sensors for ADHD Hyperactive-Impulsive Type among Children
T. Kumar and M. B. Malarvili

Chapter 20 Security of Medical Image Information by Cryptography and Watermarking Using Python
Pallavi R. Waghmare and Jaishri M. Waghmare

Chapter 21 Integration of Biosensors and Drug Delivery Systems for Biomedical Applications
Jithu Jerin James and Sandhya K. V.

Chapter 22 Automatic Liver and Lesion Segmentation in CT Using 3-D Context Convolutional Neural Network: 3-D Context U-Net
Lida Daryani Ghazani and M. A. Balafar

Index