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A novel approach to finding the compositional differences and biomarkers in gut microbiota in type 2 diabetic patients via meta-analysis, data-mining, and multivariate analysis.

Endocrinologia, diabetes y nutricion
BACKGROUND/PURPOSE OF THE STUDY: Type 2 diabetes mellitus (T2DM)-one of the fastest globally spreading diseases-is a chronic metabolic disorder characterized by elevated blood glucose levels. It has been suggested that the composition of gut microbio...

Societal factors influencing the implementation of AI-driven technologies in (smart) hospitals.

PloS one
INTRODUCTION: The introduction of AI in healthcare promises benefits, but also faces challenges. Currently, one of these challenges is the lack of information on the societal aspects of implementing AI in healthcare. This study aims to: 1) identify w...

Development and validation of an interpretable longitudinal preeclampsia risk prediction using machine learning.

PloS one
Preeclampsia is a pregnancy-specific disease characterized by new onset hypertension after 20 weeks of gestation that affects 2-8% of all pregnancies and contributes to up to 26% of maternal deaths. Despite extensive clinical research, current predic...

Protocol for evaluating the cost-effectiveness of Mongolia's sugar-sweetened beverages tax using double machine learning.

PloS one
Elevated consumption of sugar-sweetened beverages (SSBs) has been associated with an increase in obesity, type 2 diabetes, and other non-communicable diseases (NCDs), a significant health and economic burden on Mongolia. To address this, the governme...

Machine learning-based coronary heart disease diagnosis model for type 2 diabetes patients.

Frontiers in endocrinology
BACKGROUND: To establish a classification model for assisting the diagnosis of type 2 diabetes mellitus (T2DM) complicated with coronary heart disease (CHD).

The impact of multipollutant exposure on hepatic steatosis: a machine learning-based investigation into multipollutant synergistic effects.

Frontiers in public health
INTRODUCTION: This study examines the synergistic effects of multi-pollutant exposure on hepatic lipid accumulation in non-alcoholic fatty liver disease (NAFLD) through the application of an explainable machine learning framework. This approach addre...

Sarcopenia prediction model based on machine learning and SHAP values for community-based older adults with cardiovascular disease in China.

Frontiers in public health
BACKGROUND: Sarcopenia (SP), is recognized as a complication of cardiovascular disease (CVD), but few relevant diagnostic models have been developed. This study aims to establish an interpretable diagnostic model for the occurrence of SP in older adu...

Intelligent diagnosis of thyroid nodules with AI ultrasound assistance and cytology classification.

Frontiers in endocrinology
OBJECTIVE: Accurate evaluation of thyroid nodules is crucial for effective management; however, methods such as ultrasonography and Fine Needle Aspiration Cytology (FNAC) can be subjective and operator-dependent. Indeterminate thyroid nodules (ITNs) ...