Artificial neural networks in nuclear medicine.
An analysis of the accessible literature on the diagnostic applicability of artificial neural networks in coronary artery disease and pulmonary embolism appears to be comparative to the diagnosis of experienced doctors dealing with nuclear medicine. Differences in the employed models of artificial neural networks indicate a constant search for the most optimal parameters, which could guarantee the ultimate accuracy in neural network activity. The diagnostic potential within systems containing artificial neural networks proves this calculation tool to be an independent or/and an additional device for supporting a doctor's diagnosis of artery disease and pulmonary embolism.
Swietlik
Dariusz
D
Laboratory of Radiological Informatics Medical University, Gdansk, Poland. dswietlik@op.pl
Bandurski
Tomasz
T
Lass
Piotr
P
D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D003324:Coronary Artery Disease / Q000175:diagnosis / Q000000981:diagnostic imaging*; D020000:Decision Support Systems, Clinical; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016571:Neural Networks, Computer; D009683:Nuclear Medicine / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods; D011655:Pulmonary Embolism / Q000175:diagnosis / Q000000981:diagnostic imaging*; D011877:Radionuclide Imaging