Full Description
This book covers the latest research studies regarding Explainable Machine Learning used in multimedia-based healthcare applications. In this context, the content includes not only introductions for applied research efforts but also theoretical touches and discussions targeting open problems as well as future insights. In detail, a comprehensive topic coverage is ensured by focusing on remarkable healthcare problems solved with Artificial Intelligence. Because today's conditions in medical data processing are often associated with multimedia, the book considers research studies with especially multimedia data processing.
Contents
Foreword.- Preface.- Acknowledgement.- Table of Contents.- Chapter 1:.- Automatic Fetal Motion Detection from Trajectory of US Videos Based on YOLOv5 and LSTM.- Chapter 2:.- Explainable Machine Learning (XML) for Multimedia-based Healthcare Systems: Opportunities, Challenges, Ethical and Future Prospects.- Chapter 3:.- Ensemble deep learning architectures in bone cancer detection based on Medical Diagnosis in Explainable Artificial Intelligence.- Chapter 4:.- Digital dermatitis disease classification utilizing visual feature extraction and various machine learning techniques by explainable AI.- Chapter 5:.- Explainable Machine Learning in Healthcare.- Chapter 6:.- Explainable Artificial Intelligence with Scaling Techniques to Classify Breast Cancer Images.- Chapter 7:.- A Novel Approach of COVID -19 Estimation Using GIS and Kmeans Clustering: A Case of GEOAI.- Chapter 8:.- A Brief Review of Explainable Artificial Intelligence Reviews and Methods.- Chapter 9:.- Systematic Literature Review In Using Big Data Analytics And XAI Applications In Medical.- Chapter 10:.- Using Explainable Artificial Intelligence In Drug Discovery: A Theoretical Research.- Chapter 11:.- Application of Interpretable Artificial Intelligence enabled Cognitive Internet of Things for COVID-19 Pandemics.- Chapter 12:.- Remote Photoplethysmography: Digital Disruption in Health Vital Acquisition.
