PT  - JOURNAL ARTICLE
AU  - Amato, Filippo
AU  - López, Alberto
AU  - Peña-Méndez, Eladia María
AU  - Vaňhara, Petr
AU  - Hampl, Aleš
AU  - Havel, Josef
TI  - Artificial neural networks in medical diagnosis
DP  - 2013 Jul 31
TA  - Journal of Applied Biomedicine
PG  - 47--58
VI  - 11
IP  - 2
AID - 10.2478/v10136-012-0031-x
IS  - 1214021X
AB  - 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.