Providing a unique and integrated compendium of both current and emerging machine-learning paradigms in the vital field of health informatics, this work by leading experts reflects the diversity and complexity of this multi-disciplinary area of research.
The book is a unique effort to represent a variety of techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. The book provides a unique compendium of current and emerging machine learning paradigms for healthcare informatics and reflects the diversity, complexity and the depth and breath of this multi-disciplinary area. The integrated, panoramic view of data and machine learning techniques can provide an opportunity for novel clinical insights and discoveries.
Inhaltsverzeichnis
From the Contents. - Introduction to Machine Learning in Healthcare Informatics. - Wavelet-Based Machine Learning Techniques for ECG Signal Analysis. - Application of Fuzzy Logic Control for Regulation of Glucose Level of Diabetic Patient. - A Study on Machine Learning in EEG Signal Analysis.
