Machine Learning for Health Informatics State-of-the-Art and Future Challenges
Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concert...
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| Format: | eBook |
| Language: | English |
| Published: |
Cham
Springer International Publishing
2016, 2016
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| Edition: | 1st ed. 2016 |
| Series: | Lecture Notes in Artificial Intelligence
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Machine Learning for Health Informatics
- Bagging Soft Decision Trees
- Grammars for Discrete Dynamics
- Empowering Bridging Term Discovery for Cross-domain Literature Mining in the TextFlows Platform
- Visualisation of Integrated Patient-Centric Data as Pathways: Enhancing Electronic Medical Records in Clinical Practice
- Deep learning trends for focal brain pathology segmentation in MRI
- Differentiation between Normal and Epileptic EEG using K-Nearest-Neighbors Technique
- Survey on Feature Extraction and Applications of Biosignals
- Argumentation for knowledge representation, conflict resolution, defeasible inference and its integration with machine learning
- Machine Learning and Data mining Methods for Managing Parkinson’s Disease
- Challenges of Medical Text and Image Processing: Machine Learning Approaches
- Visual Intelligent Decision Support Systems in the medical field: design and evaluation.