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Efficiency of a deep learning-based artificial intelligence diagnostic system in spontaneous intracerebral hemorrhage volume measurement.

BMC medical imaging
BACKGROUND: Accurate measurement of hemorrhage volume is critical for both the prediction of prognosis and the selection of appropriate clinical treatment after spontaneous intracerebral hemorrhage (ICH). This study aimed to evaluate the performance ...

Unveiling functions of the visual cortex using task-specific deep neural networks.

PLoS computational biology
The human visual cortex enables visual perception through a cascade of hierarchical computations in cortical regions with distinct functionalities. Here, we introduce an AI-driven approach to discover the functional mapping of the visual cortex. We r...

Automating the Clinical Assessment of Independent Wheelchair Sitting Pivot Transfer Techniques.

Topics in spinal cord injury rehabilitation
BACKGROUND: Using proper transfer technique can help to reduce forces and prevent secondary injuries. However, current assessment tools rely on the ability to subjectively identify harmful movement patterns.

Intracorporeal Versus Extracorporeal Robot-assisted Kidney Autotransplantation: Experience of the ERUS RAKT Working Group.

European urology
BACKGROUND: Kidney autotransplantation is a useful technique to be reserved for cases in which kidney function is compromised by a complex anatomical configuration, such as long ureteral strictures and renal vascular anomalies not suitable for in sit...

Identifying resting state differences salient for resilience to chronic pain based on machine learning multivariate pattern analysis.

Psychophysiology
Studies have documented behavior differences between more versus less resilient adults with chronic pain (CP), but the presence and nature of underlying neurophysiological differences have received scant attention. In this study, we attempted to iden...

Vesseg: An Open-Source Tool for Deep Learning-Based Atherosclerotic Plaque Quantification in Histopathology Images-Brief Report.

Arteriosclerosis, thrombosis, and vascular biology
Objective: Manual plaque segmentation in microscopy images is a time-consuming process in atherosclerosis research and potentially subject to unacceptable user-to-user variability and observer bias. We address this by releasing Vesseg a tool that inc...

Uncovering structured responses of neural populations recorded from macaque monkeys with linear support vector machines.

STAR protocols
When a mammal, such as a macaque monkey, sees a complex natural image, many neurons in its visual cortex respond simultaneously. Here, we provide a protocol for studying the structure of population responses in laminar recordings with a machine learn...

Estimated Artificial Neural Network Modeling of Maximal Oxygen Uptake Based on Multistage 10-m Shuttle Run Test in Healthy Adults.

International journal of environmental research and public health
We aimed to develop an artificial neural network (ANN) model to estimate the maximal oxygen uptake (VOmax) based on a multistage 10 m shuttle run test (SRT) in healthy adults. For ANN-based VOmax estimation, 118 healthy Korean adults (59 men and 59 w...

Machine learning using clinical data at baseline predicts the efficacy of vedolizumab at week 22 in patients with ulcerative colitis.

Scientific reports
Predicting the response of patients with ulcerative colitis (UC) to a biologic such as vedolizumab (VDZ) before administration is an unmet need for optimizing individual patient treatment. We hypothesized that the machine-learning approach with daily...

Potential of high dimensional radiomic features to assess blood components in intraaortic vessels in non-contrast CT scans.

BMC medical imaging
BACKGROUND: To assess the potential of radiomic features to quantify components of blood in intraaortic vessels to non-invasively predict moderate-to-severe anemia in non-contrast enhanced CT scans.