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Uric Acid

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Blood metabolic signatures of hikikomori, pathological social withdrawal.

Dialogues in clinical neuroscience
BACKGROUND: A severe form of pathological social withdrawal, 'hikikomori,' has been acknowledged in Japan, spreading worldwide, and becoming a global health issue. The pathophysiology of hikikomori has not been clarified, and its biological traits re...

The association between serum uric acid to creatinine ratio and renal disease progression in type 2 diabetic patients in Chinese communities.

Journal of diabetes and its complications
AIMS: Serum uric acid (UA) increases in patients with kidney disease due to the impaired UA clearance. The present study sought to evaluate the association between UA/creatinine ratio (UA/Cr) and renal disease progression in patients with type 2 diab...

Employing biochemical biomarkers for building decision tree models to predict bipolar disorder from major depressive disorder.

Journal of affective disorders
BACKGROUND: Conventional biochemical parameters may have predictive values for use in clinical identification between bipolar disorder (BD) and major depressive disorder (MDD).

Fuzzy controller based E-nose classification of Sitophilus oryzae infestation in stored rice grain.

Food chemistry
Fuzzy controller artmap based algorithms via E-nose selective metal oxides sensor (MOS) data was applied for classification of S. oryzae infestation in rice grains. The screened defuzzified data of selective sensors was further applied to detect S. o...

Disability in multiple sclerosis is associated with age and inflammatory, metabolic and oxidative/nitrosative stress biomarkers: results of multivariate and machine learning procedures.

Metabolic brain disease
The aim of this study was to evaluate the immune-inflammatory, metabolic, and nitro-oxidative stress (IM&NO) biomarkers as predictors of disability in multiple sclerosis (MS) patients. A total of 122 patients with MS were included; their disability w...

Deep learning computer vision algorithm for detecting kidney stone composition.

BJU international
OBJECTIVES: To assess the recall of a deep learning (DL) method to automatically detect kidney stones composition from digital photographs of stones.

Machine Learning to Identify Metabolic Subtypes of Obesity: A Multi-Center Study.

Frontiers in endocrinology
BACKGROUND AND OBJECTIVE: Clinical characteristics of obesity are heterogenous, but current classification for diagnosis is simply based on BMI or metabolic healthiness. The purpose of this study was to use machine learning to explore a more precise ...

Prediction of the composition of urinary stones using deep learning.

Investigative and clinical urology
PURPOSE: This study aimed to predict the composition of urolithiasis using deep learning from urinary stone images.