Obesity

First trimester prediction of gestational diabetes mellitus by machine learning in twin pregnancies.

INTRODUCTION: We aimed to develop a machine learning model for first-trimester prediction of gestational diabetes mellitus (GDM) in twin pregnancies using a prospective international, multi-center cohort and identify useful predictive markers. METHODS: Pregnant women with two live fetuses were enrolled at 11 + 0 to 13 + 6 weeks' gestation and followed until delivery. GDM was diagnosed at 24-28 wee...

Ambient Air Pollution, Greenness and Frailty in an Elder Asian Population: A Multi-Center Study with Long-Term Exposure.

BACKGROUND: Long-term exposure to air pollution has been linked to adverse health outcomes in older adults; however, its association with frailty, particularly the potential protective role of environmental factors such as greenness, remains insufficiently investigated. METHODS: Data from the Healthy Aging Longitudinal Study in Taiwan, which included 5336 community-dwelling individuals aged 55 yea...

Preoperative Neuroimaging Markers, Clinical Severity Measures, and Shunt Characteristics for Predicting Shunt Revision in Idiopathic Intracranial Hypertension: An Explainable Machine-Learning Study.

BACKGROUND AND PURPOSE: Surgical shunt placement is a common treatment for idiopathic intracranial hypertension (IIH) but is hampered by high revision...

Enhancing dietary management and nutritional analysis through deep learning: a multi-model approach for food classification and volume estimation.

Nutrition and diet play pivotal roles in fostering a healthy lifestyle. Effective dietary management requires precise identification and analysis of c...

Leveraging machine learning to predict de novo skin malignancy following lung transplantation.

AIMS: This study aimed to predict post-transplant malignancy risks at multiple levels among lung transplant recipients using machine learning (ML) and...

ShenLingBaiZhu powder ameliorates obesity and atherosclerosis by inhibiting inflammation and apoptosis through the suppression of the TLR4/NF-κB pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: ShenLingBaiZhu Powder (SLBZP) is a renowned traditional Chinese medicinal formula that has been historically and clini...

Unveiling the relationship between stress-hyperglycemia ratio and cardiometabolic multimorbidity risk using interpretable machine learning.

BACKGROUND: Cardiometabolic multimorbidity (CMM) is the simultaneous manifestation of multiple cardiovascular and metabolic diseases, and it has arise...

Semi-Supervised Fatty Liver Classification Using Attention-Based Graph Neural Network Models.

BACKGROUND: Fatty liver disease is a common condition linked to metabolic syndrome, cardiovascular diseases, and liver cirrhosis, and timely, accurate...

From Clusters to Outcomes: Machine Learning-Based Phenotyping in Intermediate-High-Risk Acute Pulmonary Embolism.

Intermediate-high-risk (IHR) pulmonary embolism (PE) represents a heterogeneous group in whom guideline-based criteria may insufficiently capture biol...

Development and validation of an interpretable machine learning model for non-invasive screening of precancerous gastric lesions using symptom and lifestyle data: a multicentre cohort study.

BACKGROUND: Precancerous gastric lesions (PLGC) are a critical stage in gastric cancer progression, where timely intervention can substantially reduce...

Association of depressive symptoms with systemic immune-inflammation index and platelet parameters among survivors of myocardial infarction: a cross-sectional NHANES study enhanced by machine learning and SHAP analysis.

BACKGROUND: Inflammation is implicated in the elevated risk of depressive disorder following myocardial infarction (MI), with platelets serving as a k...

Gene Modification: Exploring the potential in treating kidney diseases.

Chronic kidney disease (CKD) is a leading cause of death worldwide. Currently available drugs slow but do not cure or prevent progression to end-stage...

Development and external validation of an interpretable machine learning-based model for obesity risk prediction in 2-18-year-old children and adolescents in Beijing and Tangshan.

BACKGROUND: The multifactorial mechanisms driving childhood obesity, a global public health challenge, are yet to be fully elucidated. We aimed to dev...

External validation of the IHXGboost-P model to predict incisional hernia after midline laparotomy.

BACKGROUND: Incisional hernia (IH) is a significant complication that occurs after midline laparotomy and is associated with high morbidity and econom...

Using Latent Dirichlet Allocation Topic Modeling to Uncover Latent Research Topics and Trends in Renal Cell Carcinoma: Bibliometric Review.

BACKGROUND: Renal cell carcinoma (RCC) is a common, often lethal kidney cancer that originates in the renal cortex. Its incidence is rising, and major...

Predicting the diabetic foot in patients with type 2 diabetes mellitus based on machine learning.

BACKGROUND: Diabetic foot (DF) is a severe complication of type 2 diabetes mellitus (T2DM), contributing to significant morbidity and healthcare costs...

Sex Differences in Alzheimer's Disease: A Systematic Review of Two Decades of Neuroimaging Research.

OBJECTIVES: Given the heterogeneous nature of Alzheimer's Disease (AD) and its higher prevalence in females, it is crucial to understand sex-related d...

Trends in health literacy discussions within primary health care research: A topic analysis using machine learning techniques.

OBJECTIVE: To reveal the intellectual framework, research trends, and gaps, and evaluate effective health literacy tools in the field of primary healt...

PODiaCarD: a prototype of a digital twin platform for the management of pediatric obesity and related cardiometabolic complications.

UNLABELLED: Childhood obesity is the main driver of early metabolic risk, predisposing to cardiovascular disease (CVD) and type 2 diabetes (T2D), whic...

Machine Learning Insights into Age-Related Sex Differences in Blood Pressure: Influence of Diabetes and Body Mass Index.

INTRODUCTION: The age-related dynamics of blood pressure (BP) arise from complex, often concurrent interactions among multiple factors (e.g., sex, typ...