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Diabetes Mellitus, Type 2

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Identification of Type 2 Diabetes Based on a Ten-Gene Biomarker Prediction Model Constructed Using a Support Vector Machine Algorithm.

BioMed research international
BACKGROUND: Type 2 diabetes is a major health concern worldwide. The present study is aimed at discovering effective biomarkers for an efficient diagnosis of type 2 diabetes.

A full pipeline of diagnosis and prognosis the risk of chronic diseases using deep learning and Shapley values: The Ravansar county anthropometric cohort study.

PloS one
Anthropometry is a Greek word that consists of the two words "Anthropo" meaning human species and "metery" meaning measurement. It is a science that deals with the size of the body including the dimensions of different parts, the field of motion and ...

Multimodal deep learning applied to classify healthy and disease states of human microbiome.

Scientific reports
Metagenomic sequencing methods provide considerable genomic information regarding human microbiomes, enabling us to discover and understand microbial diseases. Compositional differences have been reported between patients and healthy people, which co...

A deep learning model for screening type 2 diabetes from retinal photographs.

Nutrition, metabolism, and cardiovascular diseases : NMCD
BACKGROUND AND AIMS: We aimed to develop and evaluate a non-invasive deep learning algorithm for screening type 2 diabetes in UK Biobank participants using retinal images.

Panoramic tongue imaging and deep convolutional machine learning model for diabetes diagnosis in humans.

Scientific reports
Diabetes is a serious metabolic disorder with high rate of prevalence worldwide; the disease has the characteristics of improper secretion of insulin in pancreas that results in high glucose level in blood. The disease is also associated with other c...

Emulating complex simulations by machine learning methods.

BMC bioinformatics
BACKGROUND: The aim of the present paper is to construct an emulator of a complex biological system simulator using a machine learning approach. More specifically, the simulator is a patient-specific model that integrates metabolic, nutritional, and ...

Detection of diabetes from whole-body MRI using deep learning.

JCI insight
Obesity is one of the main drivers of type 2 diabetes, but it is not uniformly associated with the disease. The location of fat accumulation is critical for metabolic health. Specific patterns of body fat distribution, such as visceral fat, are close...

Intelligent type 2 diabetes risk prediction from administrative claim data.

Informatics for health & social care
Type 2 diabetes is a chronic, costly disease and is a serious global population health problem. Yet, the disease is well manageable and preventable if there is an early warning. This study aims to apply supervised machine learning algorithms for deve...

Characterizing shared and distinct symptom clusters in common chronic conditions through natural language processing of nursing notes.

Research in nursing & health
Data-driven characterization of symptom clusters in chronic conditions is essential for shared cluster detection and physiological mechanism discovery. This study aims to computationally describe symptom documentation from electronic nursing notes an...