AIMC Topic: Diabetes Mellitus

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Optimizing warfarin dosing in diabetic patients through BERT model and machine learning techniques.

Computers in biology and medicine
This study highlights the importance of evaluating warfarin dosing in diabetic patients, who require careful anticoagulation management. With rising rates of diabetes and cardiovascular diseases, understanding the factors influencing warfarin therapy...

A robust and generalized framework in diabetes classification across heterogeneous environments.

Computers in biology and medicine
Diabetes mellitus (DM) represents a major global health challenge, affecting a diverse range of demographic populations across all age groups. It has particular implications for women during pregnancy and the postpartum period. The contemporary preva...

Efficient diagnosis of diabetes mellitus using an improved ensemble method.

Scientific reports
Diabetes is a growing health concern in developing countries, causing considerable mortality rates. While machine learning (ML) approaches have been widely used to improve early detection and treatment, several studies have shown low classification a...

Unveiling diabetes onset: Optimized XGBoost with Bayesian optimization for enhanced prediction.

PloS one
Diabetes, a chronic condition affecting millions worldwide, necessitates early intervention to prevent severe complications. While accurately predicting diabetes onset or progression remains challenging due to complex and imbalanced datasets, recent ...

AI Machine Learning-Based Diabetes Prediction in Older Adults in South Korea: Cross-Sectional Analysis.

JMIR formative research
BACKGROUND: Diabetes is prevalent in older adults, and machine learning algorithms could help predict diabetes in this population.

Perspective: Multiomics and Artificial Intelligence for Personalized Nutritional Management of Diabetes in Patients Undergoing Peritoneal Dialysis.

Advances in nutrition (Bethesda, Md.)
Managing diabetes in patients on peritoneal dialysis (PD) is challenging due to the combined effects of dietary glucose, glucose from dialysate, and other medical complications. Advances in technology that enable continuous biological data collection...

Development of an interpretable machine learning model based on CT radiomics for the prediction of post acute pancreatitis diabetes mellitus.

Scientific reports
This study sought to establish and validate an interpretable CT radiomics-based machine learning model capable of predicting post-acute pancreatitis diabetes mellitus (PPDM-A), providing clinicians with an effective predictive tool to aid patient man...

Screening of obstructive sleep apnea and diabetes mellitus -related biomarkers based on integrated bioinformatics analysis and machine learning.

Sleep & breathing = Schlaf & Atmung
BACKGROUND: The pathophysiology of obstructive sleep apnea (OSA) and diabetes mellitus (DM) is still unknown, despite clinical reports linking the two conditions. After investigating potential roles for DM-related genes in the pathophysiology of OSA,...

Comprehensive bioinformatics analysis identifies metabolic and immune-related diagnostic biomarkers shared between diabetes and COPD using multi-omics and machine learning.

Frontiers in endocrinology
BACKGROUND: Diabetes and chronic obstructive pulmonary disease (COPD) are prominent global health challenges, each imposing significant burdens on affected individuals, healthcare systems, and society. However, the specific molecular mechanisms suppo...

Efficient and Effective Diabetes Care in the Era of Digitalization and Hypercompetitive Research Culture: A Focused Review in the Western Pacific Region with Malaysia as a Case Study.

Health systems and reform
There are approximately 220 million (about 12% regional prevalence) adults living with diabetes mellitus (DM) with its related complications, and morbidity knowingly or unconsciously in the Western Pacific Region (WP). The estimated healthcare cost i...