Title: Machine Learning in Healthcare and Security : Advances, Obstacles, and Solutions Author: Archana Patel, Prashant Pranav, Sarika Jain ISBN: 1032478411 / 9781032478418 Format: Hard Cover Pages: 224 Publisher: CRC Press Year: 2024 Availability: 2 to 3 weeks.
Description
Contents
This book brings together a blend of different areas of machine learning and recent advances in the area. From the use of ML in healthcare to security, this book encompasses several areas related to ML while keeping a check on traditional ML algorithms.
Machine Learning in Healthcare and Security: Advances, Obstacles, and Solutions describes the predictive analysis and forecasting techniques in different emerging and classical areas using the approaches of ML and AI. It discusses the application of ML and AI in medical diagnostic systems and deals with the security prevention aspects of ML and how it can be used to tackle various emerging security issues. This book also focuses on NLP and understanding the techniques, obstacles, and possible solutions.
This is a valuable reference resource for researchers and postgraduate students in healthcare systems engineering, computer science, cyber-security, information technology, and applied mathematics.
Preface
Part I : Natural Language Processing Using ML
Chapter 1 : Application of Classification and Regression Techniques in Bank Fraud Detection Chapter 2 : A Survey on Water Quality Monitoring and Controlling Using Different Modality of Machine Learning Model Chapter 3 : Design of Tea Ontology for Precision-based Tea Crop Yield Prediction Using Machine Learning Chapter 4 : Analyzing the Social Media Activities of Users Using Machine Learning and Graph Data Science
Part II : AI and ML in Healthcare
Chapter 5 : Deep Learning-Based Multiple Myeloma Identification Using Micro-imaging Technique Chapter 6 : Artificial Intelligence (AI) on a Rise in Healthcare Chapter 7 : Applications of Multitarget Regression Models in Healthcare Chapter 8 : XAI-based Autoimmune Disorders Detection Using Transfer Learning Chapter 9 : Wearable Smart Technologies : Changing the Future of Healthcare Chapter 10 : Different Security Breaches in Patients’ Data and Prevailing Ways to Counter Them
Part III : Security Aspects of ML
Chapter 11 : The Intersection of Biometrics Technology and Machine Learning : A Scientometrics Analysis Chapter 12 : Can ML Be Used in Cybersecurity? Chapter 13 : GAN Cryptography Chapter 14 : Security Aspects of Patient’s Data in a Medical Diagnostic System