Amato Filippo author López Alberto author Peña-Méndez Eladia María author Vaňhara Petr author Hampl Aleš author Havel Josef author text journal article 2013 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. medical diagnosis; artificial intelligence; artificial neural networks; cancer; cardiovascular diseases; diabetes 10.2478/v10136-012-0031-x https://jab.zsf.jcu.cz/artkey/jab-201302-0001.php https://jab.zsf.jcu.cz/artkey/jab-201302-0001.php continuing 11 2 47 58 2013 1214021X periodical academic journal