Computational intelligence and neuroscience
Feb 3, 2019
Zebrafish embryo fluorescent vessel analysis, which aims to automatically investigate the pathogenesis of diseases, has attracted much attention in medical imaging. Zebrafish vessel segmentation is a fairly challenging task, which requires distinguis...
IEEE journal of biomedical and health informatics
Jan 21, 2019
This paper studies the use of deep convolutional neural networks to segment heart sounds into their main components. The proposed methods are based on the adoption of a deep convolutional neural network architecture, which is inspired by similar appr...
Automated skin lesion classification in dermoscopy images is an essential way to improve the diagnostic performance and reduce melanoma deaths. Although deep convolutional neural networks (DCNNs) have made dramatic breakthroughs in many image classif...
OBJECTIVE: The objective of this study was to use machine learning in the form of a deep neural network to objectively classify paired auditory brainstem response waveforms into either: 'clear response', 'inconclusive' or 'response absent'.
Automated evaluation of a subject's neurocognitive performance (NCP) is a relevant topic in neurological and clinical studies. NCP represents the mental/cognitive human capacity in performing a specific task. It is difficult to develop the study prot...
Side effects occur when excessive or low doses of analgesics are administered compared to the required amount to mediate the pain induced during surgery. It is important to accurately assess the pain level of the patient during surgery. We proposed a...
OBJECTIVE: Intracranial pressure (ICP) is an important and established clinical measurement that is used in the management of severe acute brain injury. ICP waveforms are usually triphasic and are susceptible to artifact because of transient catheter...
There is a critical need for fast, inexpensive, objective, and accurate screening tools for childhood psychopathology. Perhaps most compelling is in the case of internalizing disorders, like anxiety and depression, where unobservable symptoms cause c...
OBJECTIVE: We aim to provide an algorithm for the detection of myocardial infarction that operates directly on ECG data without any preprocessing and to investigate its decision criteria.
Logistic regression (LR) and artificial neural networks (ANNs) are widely referred approaches in medical data classification studies. LR, a statistical fitting model, is suggested in medical problems because of its well-established methodology and co...
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