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Artificial intelligence identifies inflammation and confirms fibroblast foci as prognostic tissue biomarkers in idiopathic pulmonary fibrosis.

Human pathology
A large number of fibroblast foci (FF) predict mortality in idiopathic pulmonary fibrosis (IPF). Other prognostic histological markers have not been identified. Artificial intelligence (AI) offers a possibility to quantitate possible prognostic histo...

Deep Learning-Based Segmentation and Quantification in Experimental Kidney Histopathology.

Journal of the American Society of Nephrology : JASN
BACKGROUND: Nephropathologic analyses provide important outcomes-related data in experiments with the animal models that are essential for understanding kidney disease pathophysiology. Precision medicine increases the demand for quantitative, unbiase...

Artificial intelligence automates and augments baseline impedance measurements from pH-impedance studies in gastroesophageal reflux disease.

Journal of gastroenterology
BACKGROUND: Artificial intelligence (AI) has potential to streamline interpretation of pH-impedance studies. In this exploratory observational cohort study, we determined feasibility of automated AI extraction of baseline impedance (AIBI) and evaluat...

[Seasonal variations in 25-hydroxy vitamin D3, parathormone and alkaline phosphatase in school-aged children].

Revista chilena de pediatria
INTRODUCTION: The main role of Vitamin D is to regulate calcium metabolism, whose main source is vitamin D3 ob tained mostly from the action of ultraviolet (UV) light on the skin.

Development and Validation of a Deep Learning-Based Automatic Brain Segmentation and Classification Algorithm for Alzheimer Disease Using 3D T1-Weighted Volumetric Images.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Limited evidence has suggested that a deep learning automatic brain segmentation and classification method, based on T1-weighted brain MR images, can predict Alzheimer disease. Our aim was to develop and validate a deep learni...

Improving Accelerometry-Based Measurement of Functional Use of the Upper Extremity After Stroke: Machine Learning Versus Counts Threshold Method.

Neurorehabilitation and neural repair
BACKGROUND: Wrist-worn accelerometry provides objective monitoring of upper-extremity functional use, such as reaching tasks, but also detects nonfunctional movements, leading to ambiguity in monitoring results.

Artificial intelligence-based radiotherapy machine parameter optimization using reinforcement learning.

Medical physics
PURPOSE: To develop and evaluate a volumetric modulated arc therapy (VMAT) machine parameter optimization (MPO) approach based on deep-Q reinforcement learning (RL) capable of finding an optimal machine control policy using previous prostate cancer p...

Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography.

Scientific reports
Computed tomography (CT) is the preferred imaging method for diagnosing 2019 novel coronavirus (COVID19) pneumonia. We aimed to construct a system based on deep learning for detecting COVID-19 pneumonia on high resolution CT. For model development an...

Identification of early liver toxicity gene biomarkers using comparative supervised machine learning.

Scientific reports
Screening agrochemicals and pharmaceuticals for potential liver toxicity is required for regulatory approval and is an expensive and time-consuming process. The identification and utilization of early exposure gene signatures and robust predictive mo...