Obesity

Integration of site-specific deep learning models for automated OAR segmentation in craniospinal proton therapy: a geometric and dosimetric analysis.

PURPOSE: This study evaluated the feasibility of integrating RayStation deep learning auto-segmentation (DLS) models-originally trained for adult head and neck (HN), thorax-abdomen (TA), and male pelvis (MP) regions-for automated organs-at-risk (OARs) delineation in craniospinal irradiation (CSI) with intensity-modulated-proton-therapy (IMPT), focusing on geometric accuracy, dosimetric impact, and...

Optimizing the mathematical model and technical standards for unilateral biportal endoscopic spinal surgery through machine learning-based video analysis.

OBJECTIVE: To enhance the efficacy of the unilateral biportal endoscopic spinal procedure, the spinal triangle concept is proposed, integrating a digital model to establish standardized reference parameters and technical protocols for biportal positioning and incision delineation. METHODS: A retrospective-prospective cohort of 105 patients undergoing UBE for lumbar discectomy and unilateral spinal...

Human Sweat-Mediated Aggregation of Nanoplastics as a Driver of Dermal Exposure.

Nanoplastics inevitably interact with human sweat upon dermal contact, where their aggregation behavior governs the subsequent migration and penetrati...

Association between metal co-exposure and frailty: exploring the potential explanatory pathway of inflammation.

Frailty is a critical geriatric syndrome associated with disability and mortality, yet the associations and mechanisms between environmental metal co-...

Disparities in severe infection risk associated with systemic lupus erythematosus: evidence from a causal forest analysis.

OBJECTIVES: Severe infections are a primary cause of morbidity and premature mortality in patients with Systemic Lupus Erythematosus (SLE). Although S...

Integration of inflammatory and nutritional biomarkers with machine learning enhances prediction of progesterone response in fertility-preserving endometrial carcinoma management.

BACKGROUND: Endometrial carcinoma (EC) and atypical endometrial hyperplasia (AEH) increasingly affect young women, posing challenges for fertility pre...

Development and validation of a machine learning model for identifying liver fibrosis in MAFLD: a retrospective model development study.

BACKGROUND: Metabolic dysfunction-associated fatty liver disease (MAFLD), as the most prevalent chronic liver disease globally, is closely related to ...

Applications of traditional machine learning and deep learning algorithms in obesity prediction or classification: a systematic review of comparative performance.

This systematic review evaluated traditional machine learning (TML) and deep learning (DL) approaches for obesity prediction in longitudinal studies a...

Digital Management of Early-Onset Type 2 Diabetes: Empowerment, Challenges, and Future Outlook.

PURPOSE OF REVIEW: Early-onset type 2 diabetes (EOT2D), defined as a diabetes diagnosis before 40 years of age, is rising globally and associated with...

Using Machine Learning with the Brief Symptom Inventory to Screen for Comorbid Addictions: A Proof-of-Principle Study.

INTRODUCTION: Mental health disorders are leading causes of morbidity worldwide and often co-occur with substance use and other addictive behaviors. H...

Revolutionizing Nutrition: AI-Driven Health Solutions and Personalized Diets.

Artificial Intelligence (AI) is revolutionizing health and nutrition, significantly advancing personalized dietary management and health optimization....

Assessing the association of type 2 diabetes with skin health status: a study of the Northern Finland Birth Cohort 1966.

OBJECTIVES: There is evidence to suggest that alterations in skin health often co-occur with type 2 diabetes (T2D). However, the underlying mechanisms...

C-reactive protein-triglyceride-glucose index as a novel biomarker for type 2 diabetes mellitus association in women with a history of gestational diabetes mellitus.

OBJECTIVE: To explore the relationship between the C-reactive protein-triglyceride-glucose index (CTI) and the risk of type 2 diabetes mellitus (T2DM)...

Anthropometry-adjusted TyG indices predict diabetes, graft failure, and mortality in kidney transplant recipients.

CONTEXT: The triglyceride-glucose (TyG) index is a widely used surrogate marker of insulin resistance and associated with cardiometabolic outcomes. Ho...

Association and predictive value of preoperative high-sensitivity C-reactive protein for postoperative atrial fibrillation after video-assisted thoracoscopic lobectomy: a cohort study using the INSPIRE database.

BACKGROUND: Postoperative atrial fibrillation (POAF) is a common and serious complication following video-assisted thoracoscopic surgery (VATS), which...

A bibliometric analysis of global research trends and emerging hotspots on suicide and depression among children and adolescents.

BACKGROUND: Suicide and depression among children and adolescents represent critical global public health challenges. Despite a rapidly growing body o...

Where You Live Shapes Diabetes Risk: Multilevel Determinants of Type 2 Diabetes in the East South Central United States.

Type 2 diabetes melittus (T2DM) remains a major public health challenge in the United States, particularly in the east south central regions. his stud...

Performance of AI in Predicting the Progression of Gestational Diabetes to Type 2 Diabetes: Systematic Review and Meta-Analysis.

BACKGROUND: Gestational diabetes mellitus (GDM) significantly increases the risk of developing type 2 diabetes mellitus (T2DM) post partum, with up to...

AI-driven Chinese male facial skin phenotype profiling and its lifestyle correlation.

Concerns about facial skin health and aesthetics are increased among the male demographic, necessitating in-depth exploration of lifestyle factors on ...

Explainable machine learning integrating environmental chemical biomarkers and maternal clinical factors for prediction of hypertensive disorder of pregnancy.

Hypertensive disorders of pregnancy (HDP) represent a leading cause of maternal morbidity, yet environmental chemical contributors to HDP risk remain ...