Obesity

A predictive tool incorporating frailty scores for perioperative risk assessment in patients with spinal metastasis: a national retrospective cohort study.

BACKGROUND: Surgical treatment for spinal metastases is associated with high perioperative risk due to tumor burden, neurologic compromise, and limited physiological reserve. Frailty is a recognized predictor of adverse outcomes, yet most existing indices exclude key clinical variables. This study evaluated and enhanced the predictive performance of three frailty instruments-the 5-item Modified Fr...

Construction and validation of a machine learning model for predicting early pregnancy in patients with polycystic ovary syndrome: a retrospective cohort study.

OBJECTIVE: Polycystic ovary syndrome (PCOS) is a leading cause of female infertility, and early pregnancy outcomes in affected women are affected by multiple interactive factors; however, no well-established predictive tools are available. This study aimed to develop and validate machine learning (ML) models for predicting early pregnancy in women with PCOS and compare the predictive performance o...

Hearing Loss in Older Adults: Consistent Determinants Across Two Community-Based Cohorts in Southern China.

BACKGROUND: Hearing loss (HL) is common in older adults and is associated with substantial functional decline, yet community-based evidence on its det...

Discovery of hub genes linking oxidative stress to type 2 diabetic sarcopenia using single-cell sequencing and machine learning.

Type 2 diabetes mellitus (T2DM) and sarcopenia demonstrate a significant comorbidity, particularly in the elderly, yet the molecular mechanisms linkin...

Comprehensive and low-cost machine learning models for predicting MASLD prevalence: cross-sectional evidence from the amol cohort study (AmolCS).

Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a growing global health burden, yet early detection remains difficult, esp...

Preoperative MRI and clinical indicators for predicting meniscal repairability: a machine learning-based study.

OBJECTIVES: To develop and internally validate a radiology-centered machine-learning model using preoperative MRI and clinical characteristics to pred...

Identifying predictor factors for asthma using machine learning: evidence from the English Longitudinal Study of Ageing.

BACKGROUND: Asthma is a common chronic inflammatory airway disease. Accumulating evidence highlights the roles of demographic, lifestyle, and comorbid...

Development of a predictive model for postoperative body mass index and diabetes outcomes after metabolic bariatric surgery: retrospective cohort study.

BACKGROUND: Predicting postoperative body mass index (BMI) trajectories and long-term type 2 diabetes (T2D) remission after bariatric surgery remains ...

Development of a human-artificial intelligence collaboration-based storybook series for understanding epilepsy and supporting self-management.

Epilepsy is a chronic condition that requires ongoing self-management, including medication adherence, trigger control, lifestyle regulation, and psyc...

Processed meat intake and incident gout: Integrated evidence from epidemiology, plasma proteomics, and machine learning.

INTRODUCTION: Gout is a common metabolic inflammatory disorder whose incidence parallels modern dietary shifts. Although processed meat intake is link...

Prediction of Type 2 Diabetes Mellitus From Chest X-Rays Using a Suite of Previously Developed Chronic Disease Deep Learning Models in an Ethnically Diverse Cohort: Observational Study.

BACKGROUND: Screening for type 2 diabetes (T2D) is not optimal, leading to a large number of patients being undiagnosed. Recently, deep learning (DL) ...

Homogeneity of Liver Fat Distribution Serves as a Diagnostic Marker for Metabolic Dysfunction-Associated Steatohepatitis.

RATIONALE AND OBJECTIVES: To characterize liver fat distribution in metabolic dysfunction-associated steatohepatitis (MASH) and propose a magnetic res...

Body composition's effect on the bone-vascular axis of osteoporosis discovered in AI-based CT analysis of COPD patients.

OBJECTIVES: This study aimed to investigate the effect of body composition on the inverse relationship between vertebral bone density (T12 BMD) and to...

Machine learning-assisted prediction of obstructive sleep apnea in patients with metabolic dysfunction-associated steatotic liver disease: a multicenter study with external validation.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is closely associated with obstructive sleep apnea (OSA) through shared m...

Development and Validation of an Explainable Machine Learning Model to Assess the Prevalence Probability of Gastrointestinal Heat Retention Syndrome in Children: Cross-Sectional Study.

BACKGROUND: Health problems associated with energy metabolism imbalance have received increasing attention. Our team was the first to propose the conc...

Imaging-Derived Sarcopenic Obesity and Cardiovascular Outcomes: Insights Into Heart Failure Risk and Muscle Biology.

BACKGROUND: The prognostic value of obesity in cardiovascular disease is complex. Measures such as body mass index and waist-to-height ratio show diff...

Reframing Cardiometabolic Risk and Frailty Through Sarcopenic Obesity.

Opportunistic screening for incident cardiometabolic disease in metabolically healthy non-obese individuals: a prospective cohort study.

BACKGROUND: Metabolically healthy non-obese (MHN) individuals are considered at low cardiometabolic risk, yet a subset may harbor unfavorable visceral...

Insulin resistance surrogate indices and incident cardiovascular disease across cardiovascular-kidney-metabolic stages 0-3: a prospective cohort study.

BACKGROUND: The American Heart Association (AHA) recently proposed the concept of Cardiovascular-Kidney-Metabolic (CKM) syndrome, highlighting the str...

Decoding the molecular memory of obesity using machine learning and microRNA dynamics.