Artificial neural networks in medical diagnosis

作者：Filippo Amato, Alberto Botana López, Eladia María Peña‐Méndez, Petr Vaňhara, Aleš Hampl, Josef Havel · 发表于：Journal of Applied Biomedicine · 年份：2013 · DOI：10.2478/v10136-012-0031-x · 被引用次数：909 · 研究领域：Artificial Intelligence in Healthcare、Advanced Data Processing Techniques

An extensive amount of information is currently available to clinical specialists, ranging from details of clinical symptoms to various types of biochemical data and outputs of imaging devices. Each type of data provides information that must be evaluated and assigned to a particular pathology during the diagnostic process. To streamline the diagnostic process in daily routine and avoid misdiagnosis, artificial intelligence methods (especially computer aided diagnosis and artificial neural networks) can be employed. These adaptive learning algorithms can handle diverse types of medical data and integrate them into categorized outputs. In this paper, we briefly review and discuss the philosophy, capabilities, and limitations of artificial neural networks in medical diagnosis through selected examples.