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A Bayesian mixed effects support vector machine for learning and predicting daily substance use disorder patterns.

The American journal of drug and alcohol abuse
Substance use disorder (SUD) is a heterogeneous disorder. Adapting machine learning algorithms to allow for the parsing of intrapersonal and interpersonal heterogeneity in meaningful ways may accelerate the discovery and implementation of clinically...

Reproducible neuroimaging features for diagnosis of autism spectrum disorder with machine learning.

Scientific reports
Autism spectrum disorder (ASD) is the fourth most common neurodevelopmental disorder, with a prevalence of 1 in 160 children. Accurate diagnosis relies on experts, but such individuals are scarce. This has led to increasing interest in the developmen...

Unsupervised learning of haptic material properties.

eLife
When touching the surface of an object, its spatial structure translates into a vibration on the skin. The perceptual system evolved to translate this pattern into a representation that allows to distinguish between different materials. Here, we show...

Retzius-sparing technique independently predicts early recovery of urinary continence after robot-assisted radical prostatectomy.

Journal of robotic surgery
Robot-assisted radical prostatectomy (RARP) is the conventional surgical treatment option for localised prostate cancer. We investigated factors which may be associated with recovery of early urinary continence (EUC), including the use of the Retzius...

A Multiparametric Fusion Deep Learning Model Based on DCE-MRI for Preoperative Prediction of Microvascular Invasion in Intrahepatic Cholangiocarcinoma.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Assessment of microvascular invasion (MVI) in intrahepatic cholangiocarcinoma (ICC) by using a noninvasive method is an unresolved issue. Deep learning (DL) methods based on multiparametric fusion of MR images have the potential of preope...

Prediction of lymph node metastasis in early colorectal cancer based on histologic images by artificial intelligence.

Scientific reports
Risk evaluation of lymph node metastasis (LNM) for endoscopically resected submucosal invasive (T1) colorectal cancers (CRC) is critical for determining therapeutic strategies, but interobserver variability for histologic evaluation remains a major p...

Explaining the differences of gait patterns between high and low-mileage runners with machine learning.

Scientific reports
Running gait patterns have implications for revealing the causes of injuries between higher-mileage runners and low-mileage runners. However, there is limited research on the possible relationships between running gait patterns and weekly running mil...

Deep learning for fully automatic detection, segmentation, and Gleason grade estimation of prostate cancer in multiparametric magnetic resonance images.

Scientific reports
Although the emergence of multi-parametric magnetic resonance imaging (mpMRI) has had a profound impact on the diagnosis of prostate cancers (PCa), analyzing these images remains still complex even for experts. This paper proposes a fully automatic s...