AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Diabetes Mellitus

Showing 31 to 40 of 411 articles

Clear Filters

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...

Virtual Patients Using Large Language Models: Scalable, Contextualized Simulation of Clinician-Patient Dialogue With Feedback.

Journal of medical Internet research
BACKGROUND: Virtual patients (VPs) are computer screen-based simulations of patient-clinician encounters. VP use is limited by cost and low scalability.

Potential Use and Limitation of Artificial Intelligence to Screen Diabetes Mellitus in Clinical Practice: A Literature Review.

Acta medica Indonesiana
The burden of undiagnosed diabetes mellitus (DM) is substantial, with approximately 240 million individuals globally unaware of their condition, disproportionately affecting low- and middle-income countries (LMICs), including Indonesia. Without scree...

Diabetes and Cataracts Development-Characteristics, Subtypes and Predictive Modeling Using Machine Learning in Romanian Patients: A Cross-Sectional Study.

Medicina (Kaunas, Lithuania)
Diabetes has become a global epidemic, contributing to significant health challenges due to its complications. Among these, diabetes can affect sight through various mechanisms, emphasizing the importance of early identification and management of vi...

Risk factor assessment of prediabetes and diabetes based on epidemic characteristics in new urban areas: a retrospective and a machine learning study.

Scientific reports
To explore in depth the characteristics of the risk factors for diabetes and prediabetes pathogenesis and progression in special regions. We investigated medical data from 160 thousand cases in the newly developing urban area of a large modern city f...

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 ...

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...