Diabetes

A machine learning model for optimizing treatment of patients with poorly controlled type 2 diabetes.

BACKGROUND: Cardiorenal-protective sodium-glucose cotransporter-2 inhibitors (SGLT-2i) and glucagon-like peptide-1 receptor agonists (GLP-1RA) lack selection guidance. We aimed to build a SGLT-2i/GLP-1RA Decision Score (TiP DecScore) to tailor selection between them. METHODS: We developed the TiP DecScore in type 2 diabetes (T2D) patients receiving either therapy from the China Metabolic Analytics...

Application of machine learning approaches to develop predictive models for diabetes and hypertension among Bangladeshi Adults.

With rapid urbanization, lifestyle changes, and an aging population, non-communicable diseases (NCDs), including hypertension and diabetes, pose significant public health challenges in Bangladesh and many other low- and middle-income countries. This study used machine learning (ML) approaches to develop predictive models for hypertension and diabetes among Bangladeshi adults. Bangladesh Demographi...

Smart insulin dosage software based on trend arrows: an effective method for controlling hyperglycemia in hospitalized diabetic patients in non-endocrine departments (a randomized controlled trial).

Epidemiological Trajectories and Quality of Care Disparities of MASLD in Asia, 1990-2023.

BACKGROUND: To characterize temporal and geographic patterns of metabolic dysfunction-associated steatotic liver disease (MASLD) across Asia from 1990...

Exploring the feasibility of near-infrared spectroscopy and machine learning for detecting cardiovascular diseases and diabetes mellitus in fingernails.

Cardiovascular diseases (CVDs) and diabetes mellitus (DM) are significant conditions that impact lives around the globe. Frequently employed methods f...

Deep-Q-Network in Multiview Ensemble Learning to Predict Anti-diabetic Peptide and Diabetic Types.

Diabetes mellitus disease has become a significant human health concern globally, causing cardiovascular complications, kidney disease, cerebrovascula...

AI-integrated smartphone platform enables POC dual-channel glucose monitoring with an indicator-free nanozyme gel kit.

We developed an indicator-free, dual-mode glucose monitoring platform by synthesizing glucose oxidase (GOX)-templated MnO2 nanosheets via a microwave-...

Machine learning-predicted insulin resistance is a risk factor for 12 types of cancer.

Insulin resistance is suggested to be a risk factor for cancer; however, large-scale epidemiological evidence linking insulin resistance to cancer rem...

Risk Prediction of Chronic Kidney Disease Progression in Type 2 Diabetes Mellitus Across Diverse Populations.

Chronic kidney disease (CKD) is a common complication of type 2 diabetes mellitus (T2DM), with limited predictive tools for individualized prognosis, ...

Reliable discrimination of type 1 and type 2 diabetes by flow-through leukocyte-endothelium interactions exploiting advanced hydrodynamic detection parameters.

Type 1 (T1D) and type 2 diabetes (T2D) are both associated with chronic inflammation and endothelial dysfunction, yet their discrimination based on co...

Corrigendum to "Predicting postpartum glucose intolerance in women with gestational diabetes mellitus in primary care: A machine learning approach using XGBoost and SHAP values" [Diabetes Res. Clin. Pract. 232 (2026) 113098].

An allostatic load domain-specific metabolic profile in young adults: The African-PREDICT study.

Allostatic load scores (ALSs) quantify the cumulative physiological burden of sustained stress across neuro-endocrine, metabolic, cardiovascular and i...

Association of cardiovascular-kidney-metabolic syndrome stages with MASLD prevalence and liver fibrosis severity: evidence from traditional and machine learning approaches.

INTRODUCTION: Cardiovascular-Kidney-Metabolic (CKM) syndrome reflects the convergence of cardiovascular, renal, and metabolic disorders. Metabolic dys...

Neuromodulation using Bioelectronics-enabled therapies to combat insulin resistance and its comorbidities.

INTRODUCTION: Insulin resistance is a complex metabolic disorder that involves multiple molecular pathways to disrupt insulin signaling and is associa...

Surface-based cortical thickness and gyrification mapping with data-driven prediction of cognitive impairment in prediabetes.

BACKGROUND: Prediabetes is a serious health condition characterized by blood glucose levels that are higher than normal but not high enough for a diag...

Feasibility of Integrating Urinary Proteomics and Machine Learning for Diagnosing Diabetic Nephropathy.

Diabetic nephropathy (DN) represents the predominant microvascular complication associated with diabetes mellitus; however, existing diagnostic techni...

Identification of VEGFB associated with NKT cells in diabetic foot ulcers: Single-cell analysis and machine learning.

The management options for diabetic foot are restricted, and the outlook is unfavorable. Immune cells have been implicated in diabetic foot ulcer (DFU...

Identification of a type 1 diabetes-associated T cell receptor repertoire signature from the human peripheral blood.

Type 1 diabetes (T1D) is a T cell-mediated disease with a strong immunogenetic human leukocyte antigen (HLA) dependence. HLA allelic influence on the ...

Research on the Application Value of Blood Plasma Autofluorescence Spectroscopy Model Constructed by Machine Learning Algorithms in Identifying the Types of Post-operative Kidney Transplantation Injury.

BACKGROUND: This study aimed to assess the value of blood plasma autofluorescence spectroscopy in classifying renal injury after renal transplantation...

From Telemedicine to Early Warning: Embedding Artificial Intelligence in Remote Follow-Up of Diabetic Foot Ulcers.