Artificial neural networks (ANNs) for differential diagnosis of interstitial lung disease : results of a simulation test with actual clinical cases1

Performance Evaluation of Radiologists with Artificial Neural Network for Differential Diagnosis of Intra-Axial Cerebral Tumors on MR Images

“…The diagnostic performance of each radiologist improved with the use of the ANN, especially for the radiologists who were not yet board certified (Tables 2 and 3). This finding was in accordance with several previous studies [1][2][3][4][5][6][7][8][9] and indicates that the ANN may be helpful in particular for readers with limited clinical experience. It can be reasonably speculated that the ANN would help precertification radiologists who might fail to recognize important clinical or MR features by suggesting they reconsider certain diagnostic decisions through the careful merging of MR features and clinical parameters.…”

“…ANNs have been reported to improve the diagnostic performance of radiologists in several fields. [1][2][3][4][5][6][7][8][9] The objectives of this study were to construct an ANN for the differential diagnosis of intra-axial cerebral tumors on MR images and to evaluate the effect of ANN outputs on radiologists' diagnostic performance.…”

Computer-Aided Diagnosis Systems for Brain Diseases in Magnetic Resonance Images

“…A computerized method that is capable of providing objective information about an image may assist radiologists in the classification of brain tumors. ANNs have been reported to improve the diagnostic performance of radiologists in several fields [94][95][96][97][98][99][100][101][102]. A few groups applied ANNs including a self-organizing maps (SOMs) to classify intracranial diseases including brain tumors, pituitary adenoma, craniopharyngioma, and Rathke's cleft cyst.…”

Expert System for Disease Diagnosis: An Attempt to Develop Ai Based Diagnostic System

“…Within the computer this knowledge is often represented by some rules or as data and depending on problem requirement, these rules can be evoked [1].Expert system can help physicians by advising them about unrecognized data needs of a diagnosis, analysing and treatment procedures by the helps of tools comprises of symptoms, conditions and finally come out with actual result. The significant issue in building up a medical decision support neural network is relies on substantial number of training cases which are required to pick up a decent diagnostic ability [2]. These substantial numbers of training cases may not be generally available always.…”