BACKGROUND: Various types of robots have already been successfully used in medical care, and the use of new technologies is also playing an increasing role in the area of sexuality. Sex robots are marketed as advanced sex toys and sex dolls with arti...
BACKGROUND: Recently, a biologically-driven psychosis classification (B-SNIP Biotypes) was derived using brain-based cognitive and electrophysiological markers. Here, we characterized a local functional-connectivity measure, regional homogeneity (ReH...
Procrastination takes a considerable toll on people's lives, the economy and society at large. Procrastination is often a consequence of people's propensity to prioritize their immediate experiences over the long-term consequences of their actions. T...
Computer assisted surgery (Abingdon, England)
Aug 19, 2019
Automatic segmentation of prostate magnetic resonance (MR) images has great significance for the diagnosis and clinical application of prostate diseases. It faces enormous challenges because of the low contrast of the tissue boundary and the small ef...
BMC medical informatics and decision making
Aug 19, 2019
BACKGROUND: Machine learning has been used extensively in clinical text classification tasks. Deep learning approaches using word embeddings have been recently gaining momentum in biomedical applications. In an effort to automate the identification o...
Trichomonas vaginalis (T. vaginalis) detection remains an unsolved problem in using of automated instruments for urinalysis. The study proposes a machine learning (ML)-based strategy to increase the detection rate of T. vaginalis in urine. On the bas...
Virchows Archiv : an international journal of pathology
Aug 17, 2019
Estimation of risk of recurrence in early-stage oral tongue squamous cell carcinoma (OTSCC) remains a challenge in the field of head and neck oncology. We examined the use of artificial neural networks (ANNs) to predict recurrences in early-stage OTS...
BACKGROUND AND PURPOSE: Advanced imaging analysis for the prediction of tumor biology and modelling of clinically relevant parameters using computed imaging features is part of the emerging field of radiomics research. Here we test the hypothesis tha...
PURPOSE: An automated accurate segmentation for dynamic contrast-enhanced magnetic resonance (DCE-MR) image sequences is essential for quantification of renal function. A self-supervised strategy is proposed for fully automatic segmentation of the re...
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