AI-Driven Innovations in Digital Healthcare

The best cure for each patient requires the specific testing, and in recent years promising AI-based solutions have emerged and accelerated support for medical staff and doctors in health treatments. So, these solutions must be administered early in the course of the disease prediction in order to do any good for patients. The book comprehensive guide explores the AI-driven innovations, challenges, benefits, and applications in the digital healthcare sector..

This book also serves as a comprehensive introduction for researchers, practitioners, and enthusiasts seeking to understand the implications of AI-Driven Innovations in Digital Healthcare and other sciences.

AI-Driven Innovations in Digital Healthcare: Emerging Trends, Challenges, and Applications This book is scheduled to be published and indexed by IGI Global (formerly Idea Group Inc.), an international academic publisher of the "Information Science Reference" (formerly Idea Group Reference), "Medical Robotics Science Reference," "AI Science Reference," and "Diagnostics Science Reference" imprints. IGI Global specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, agriculture, education, social science, medicine and healthcare, business and management, information science and technology, diagnostics, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com. This publication is anticipated to be released in 2024.

No Publication Charge

All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome Before You Write

All inquiries about submissions should be emailed to

Prof. Dr. Alex Khang PH

• Professor of IT, AI & Data Scientist
• Cloud and Database Expert
• IT Workforce Development Consultant
• Global Research Institute of Technology and Engineering
• North Carolina, United States
• ORCID: 0000-0001-8379-4659
• WhatsApp: +84-09-3235-7799
• alex.khang@outlook.com

We invite rofessors, doctors, scholars, engineers, scientist, specialists, friends, scholars, experts, colleagues, students, and IT community around the world to contribute to the book "AI-Driven Innovations in Digital Healthcare: Emerging Trends, Challenges, and Applications". The scope of the book includes, but is not limited to the following topics:

• AI-Driven Innovations in Healthcare Industry: Emerging Trends, Challenges, and Applications
• Role of Cutting-Edge Technologies in Digital Healthcare
• Fugure of Solutions, and Applications in Healthcare Industry
• Deep Learning Frameworks in Healthcare Industry
• Patient's Hate Speech Detection using Recurrent Neural Networks (RNN)
• Enhancing Healthcare Image Segmentation Accuracy Using Deep Learning Techniques
• Cardiovascular Diseases-AI Clinical Decision Support System (AI-CDSS)
• Medical Robotics and AI-Assisted Diagnostics Challenges for Smart Sustainable Healthcare
• Investigation on Identification of Three-Compartment Model for the Benchmark Pharmacokinetic System
• AI Driven System for Early Detection and Diagnosis of Cataracts by Image Recognition and ML Algorithms
• Advancements in Medical Robotics and AI Assisted Diagnostics Transforming the Healthcare Industry
• Extreme Gradient Boosting Algorithm to Predict the Post-Translational Modification (PTM) Glycosylation
• COVID-19 Deep Learning Approach for Diagnosis: Deep Learning Method
• Implementation and Impact of Chatbots and Virtual Assistants in Healthcare System
• Implications of AI-Driven Decision-Making in the Pharmaceutical Industry
• Magnetic Resonance Imaging (MRI) Brain Tumors Diagnosis Methods
• Functional Magnetic Resonance Imaging: An Overview of Technical Advances and Clinical Applications
• Internet of Things-Combined Deep Learning for Electroencephalography-based E-Healthcare
• Federated Learning for Breast Cancer Classification: Study of Decentralized Mammography Classification
• Mental Health Crises in the COVID-19 Era: Using AI Algorithms and Feature Selection Strategies
• Implementation of Machine Learning for Smart Wearable in Healthcare Sector
• The Ongoing Advancements in Surgical Robotics: Transforming the Landscape of Surgery
• Healthcare Smart Sensors - Applications, Trends and Future Outlook
• Internet of Medical Laboratory Things (IoMLTs) in High-Tech Healthcare Industry
• Healthcare and Medical Cloud-Based Data Management System
• Big Data and Data Analytics for Digital Healthcare
• Monitoring Patient's Healthcare using Aritificial Intelligence and Internet of Things
• AI Models and Green Computing in Digital Healthcare Industry
• Quatum Computing Healthcare Industry: Innovations and Applications
• Cybersecurity and Cloud Computing for Digital Healthcare Industry