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Aqueous autotaxin and TGF-βs are promising diagnostic biomarkers for distinguishing open-angle glaucoma subtypes.

Scientific reports
The purpose of this study is to examine if aqueous autotaxin (ATX) and TGF-β levels could be used for differentiating glaucoma subtypes. This prospective observational study was performed using aqueous humor samples obtained from 281 consecutive pati...

Deep learning identifies partially overlapping subnetworks in the human social brain.

Communications biology
Complex social interplay is a defining property of the human species. In social neuroscience, many experiments have sought to first define and then locate 'perspective taking', 'empathy', and other psychological concepts to specific brain circuits. S...

CT image segmentation for inflamed and fibrotic lungs using a multi-resolution convolutional neural network.

Scientific reports
The purpose of this study was to develop a fully-automated segmentation algorithm, robust to various density enhancing lung abnormalities, to facilitate rapid quantitative analysis of computed tomography images. A polymorphic training approach is pro...

Machine learning predicts lymph node metastasis of poorly differentiated-type intramucosal gastric cancer.

Scientific reports
To construct a machine learning algorithm model of lymph node metastasis (LNM) in patients with poorly differentiated-type intramucosal gastric cancer. 1169 patients with postoperative gastric cancer were divided into a training group and a test grou...

Deep learning-based automatic delineation of the hippocampus by MRI: geometric and dosimetric evaluation.

Radiation oncology (London, England)
BACKGROUND: Whole brain radiotherapy (WBRT) can impair patients' cognitive function. Hippocampal avoidance during WBRT can potentially prevent this side effect. However, manually delineating the target area is time-consuming and difficult. Here, we p...

Face Hallucination With Finishing Touches.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Obtaining a high-quality frontal face image from a low-resolution (LR) non-frontal face image is primarily important for many facial analysis applications. However, mainstreams either focus on super-resolving near-frontal LR faces or frontalizing non...

Artificial Intelligence-Powered Measurement of Left Ventricular Ejection Fraction Using a Handheld Ultrasound Device.

Ultrasound in medicine & biology
The aim of this study was to assess the accuracy of an algorithm for automated measurement of left ventricular ejection fraction (LVEF) available on handheld ultrasound devices (HUDs). One hundred twelve patients admitted to the cardiology department...

Development of a machine learning model for predicting pediatric mortality in the early stages of intensive care unit admission.

Scientific reports
The aim of this study was to develop a predictive model of pediatric mortality in the early stages of intensive care unit (ICU) admission using machine learning. Patients less than 18 years old who were admitted to ICUs at four tertiary referral hosp...

Deep learning based prediction of prognosis in nonmetastatic clear cell renal cell carcinoma.

Scientific reports
Survival analyses for malignancies, including renal cell carcinoma (RCC), have primarily been conducted using the Cox proportional hazards (CPH) model. We compared the random survival forest (RSF) and DeepSurv models with the CPH model to predict rec...

Foveal avascular zone segmentation in optical coherence tomography angiography images using a deep learning approach.

Scientific reports
The purpose of this study was to introduce a new deep learning (DL) model for segmentation of the fovea avascular zone (FAZ) in en face optical coherence tomography angiography (OCTA) and compare the results with those of the device's built-in softwa...