Obesity

Does restrictive anorexia nervosa impact brain aging? A machine learning approach to estimate age based on brain structure.

Anorexia nervosa (AN), a severe eating disorder marked by extreme weight loss and malnutrition, leads to significant alterations in brain structure. This study used machine learning (ML) to estimate brain age from structural MRI scans and investigated brain-predicted age difference (brain-PAD) as a potential biomarker in AN. Structural MRI scans were collected from female participants aged 10-40 y...

Type 2 Diabetes Mellitus Remission, Dream or Reality? A Narrative Review of Current Evidence and Integrated Care Strategies.

Type 2 diabetes mellitus (T2DM) is a global health priority, with an estimated 629 million people projected to be affected by the year 2045. T2DM significantly increases the risk of atherosclerotic cardiovascular disease and other complications. Hyperglycaemia imprints early molecular and cellular changes, often termed "metabolic memory", predisposing individuals to long-term microvascular and mac...

Availability and Use of Digital Technology Among Women With Polycystic Ovary Syndrome: Scoping Review.

BACKGROUND: Polycystic ovary syndrome (PCOS) is a common endocrinopathy among women that requires self-management to improve mental and physical healt...

Atrial Fibrillation Recurrence After Catheter Ablation: The Puzzle We Have and the Pieces We Need.

Atrial fibrillation (Afib) recurrence following catheter ablation (CA) remains a significant challenge within the electrophysiology community, potenti...

A Mortality Risk Prediction Model for Septic Shock in Patients Aged ≥50: Role of Norepinephrine Index and Procalcitonin.

BACKGROUND: Septic shock is a high-mortality syndrome, particularly in patients aged 50 and older. Predicting mortality in this population is challeng...

Identification and validation of blood leukocyte DNA methylation biomarkers for early detection of colorectal neoplasm.

BACKGROUND: Identifying high-risk populations for colorectal cancer (CRC) is critical for precise screening. This study aimed to develop a novel risk ...

Evaluating the relationship between environmental chemicals and obesity: Evidence from a machine learning perspective.

Environmental chemicals are increasingly recognized as important contributors to obesity, yet the number of studies evaluating this relationship remai...

Machine learning-based prediction of respiratory depression during sedation for liposuction.

Procedural sedation is often performed by non-anesthesiologists in various settings and can lead to respiratory depression. A tool that enables early ...

Out-of-distribution reject option method for dataset shift problem in early disease onset prediction.

Machine learning is increasingly used to predict lifestyle-related disease onset using health and medical data. However, its predictive accuracy for u...

Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis.

Diabetes Mellitus is a chronic metabolic disorder affecting a substantial global population leading to complications such as retinopathy, nephropathy,...

Development and Validation of a Lifestyle-Based 10-Year Risk Prediction Model of Colorectal Cancer for Early Stratification: Evidence from a Longitudinal Screening Cohort in China.

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide, with growing evidence linking risk to lifestyle and ...

Methodological Review of Classification Trees for Risk Stratification: An Application Example in the Obesity Paradox.

BACKGROUND: Classification trees (CTs) are widely used machine learning algorithms with growing applications in clinical research, especially for risk...

Development Of the VAMPCT Score for Predicting Mortality in CKD Patients with COVID-19.

Chronic kidney disease (CKD) patients with coronavirus disease 2019 (COVID-19) are at significant risk of death. However, clinical identification of ...

A review of enhanced biosignature immunotherapy tools for predicting lung cancer immune phenotypes using deep learning.

Cancer has increasingly been recognized as a genetic disease, influenced by lifestyle changes, dietary patterns, and environmental pollutants. Lung ca...

Momentary dietary lapse prediction for obesity management: Developing the Eating Behaviour Lapse Inventory Survey Singapore (eBLISS) and a machine learning lapse prediction model.

BACKGROUND: As the obesity prevalence continues to rise, effective interventions that promote dietary adherence and address the intricate array of fac...

A Novel and Modern Calculator to Predict Vaginal Birth after Cesarean Delivery.

Counseling patients who are considering a trial of labor after cesarean (TOLAC) is a challenging task given the risks and benefits of either approach....

Evaluation of a large language model to simplify discharge summaries and provide cardiological lifestyle recommendations.

BACKGROUND: Hospital discharge summaries are essential for the continuity of care. However, medical jargon, abbreviations, and technical language ofte...

Machine learning prediction for early-stage melanoma outcomes: recurrence-free survival, disease-specific survival, and overall survival.

This study compared machine-learning models for predicting recurrence-free survival (RFS), disease-specific survival (DSS), and overall survival (OS) ...

The Next Frontiers in Preventive and Personalized Healthcare: Artificial Intelligent-Powered Solutions.

Artificial intelligence (AI)-enabled technologies have the potential to significantly increase diagnostic accuracy, optimize treatment strategies, and...

Development and Validation of Machine Learning-Based Marker for Early Detection and Prognosis Stratification of Nonalcoholic Fatty Liver Disease.

Nonalcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease and is considered the hepatic manifestation of metabolic syndro...