Features
- Integrates computer science and clinical perspectives
- Describes various statistical and artificial intelligence techniques, including machine learning techniques such as clustering of temporal data, regression analysis, neural networks, HMM, decision trees, SVM, and data mining, all of which are techniques used widely used in health-data analysis
- Describes computational techniques such as multidimensional and multimedia data representation and retrieval, ontology, patient-data deidentification, temporal data analysis, heterogeneous databases, medical image analysis and transmission, biosignal analysis, pervasive healthcare, automated text-analysis, health-vocabulary knowledgebases and medical information-exchange
- Includes bioinformatics and pharmacokinetics techniques and their applications to vaccine and drug development
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