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Objective In this paper, the new complex-valued wavelet artificial neural network (CVWANN) was proposed for classifying Doppler signals recorded from patients and healthy volunteers. CVWANN was implemented on four different structures (CVWANN-1, -2, -3 and -4).
Objective This work presents a novel approach for the automated prediction of the aesthetic result of breast cancer conservative treatment (BCCT). Cosmetic assessment plays a major role in the study of BCCT. Objective assessment methods are being preferred to overcome the drawbacks of subjective...
Objective This study investigates the use of automated pattern recognition methods on magnetic resonance data with the ultimate goal to assist clinicians in the diagnosis of brain tumours. Recently, the combined use of magnetic resonance imaging (MRI) and magnetic resonance spectroscopic imaging...
Objectives The aim of this paper is the development of an automated method for the segmentation and quantification of inflammatory tissue of the hand in patients suffering form rheumatoid arthritis using contrast enhanced T1-weighted magnetic resonance images.
Objective This paper presents the results obtained with the innovative use of special types of artificial neural networks (ANNs) assembled in a novel methodology named IFAST (implicit function as squashing time) capable of compressing the temporal sequence of electroencephalographic (EEG) data...
Objective This study compared the diagnostic accuracy of different approaches of case-based reasoning (CBR) for the assessment of coronary artery disease (CAD) using thallium-201 myocardial perfusion scintigraphy in comparison with coronary angiography.
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