Many vision science studies employ machine learning, especially the version called "deep learning." Neuroscientists use machine learning to decode neural responses. Perception scientists try to understand how living organisms recognize objects. To th...
PURPOSE: The recognition of cystoscopic findings remains challenging for young colleagues and depends on the examiner's skills. Computer-aided diagnosis tools using feature extraction and deep learning show promise as instruments to perform diagnosti...
Water science and technology : a journal of the International Association on Water Pollution Research
Dec 1, 2018
In the present study, three different artificial intelligence based non-linear models, i.e. feed forward neural network (FFNN), adaptive neuro fuzzy inference system (ANFIS), support vector machine (SVM) approaches and a classical multi-linear regres...
Diffuse optical tomography (DOT) is a promising noninvasive imaging modality and is capable of providing functional characteristics of biological tissue by quantifying optical parameters. The DOT image reconstruction is ill-posed and ill-conditioned,...
Giornale italiano di nefrologia : organo ufficiale della Societa italiana di nefrologia
Dec 1, 2018
Health care workers need artificial intelligence. Artificial intelligence is a set of studies and techniques that tend to the realization of machines, which solve complex problems automatically, simulating or emulating human intelligence activities. ...
Artificial intelligence was recognised many years ago as a potential and powerful tool to predict disease outcome in many clinical situations. The conventional approaches using statistical methods have provided much information, but are subject to li...
Journal of the American Medical Informatics Association : JAMIA
Dec 1, 2018
OBJECTIVES: Scoring laboratory polysomnography (PSG) data remains a manual task of visually annotating 3 primary categories: sleep stages, sleep disordered breathing, and limb movements. Attempts to automate this process have been hampered by the com...
Establishing a connection between intrinsic and task-evoked brain activities is critical because it would provide a way to map task-related brain regions in patients unable to comply with such tasks. A crucial question within this realm is to what ex...
Journal of the American Medical Informatics Association : JAMIA
Dec 1, 2018
OBJECTIVE: Quantify physiologically acceptable PICU-discharge vital signs and develop machine learning models to predict these values for individual patients throughout their PICU episode.
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