Obesity

Prevalence of Lipoprotein(a) Testing in Patients With Atherosclerotic Cardiovascular Disease Within a Large Australian Cardiology Network.

BACKGROUND: Increased lipoprotein(a) (Lp[a]) is a genetically determined causal risk factor for atherosclerotic cardiovascular disease (ASCVD). Historically, Lp(a) testing has been uncommon in Australia. This study aims to assess the prevalence and trends in Lp(a) testing in Australia, and the associated patient characteristics. METHOD: This retrospective cross-sectional study examined over 1.1 mi...

Interpretable machine learning models based on CMR radiomics for predicting left ventricular diastolic dysfunction in patients with metabolic-associated steatotic liver disease and type 2 diabetes mellitus.

BACKGROUND: Obesity-induced left ventricular diastolic dysfunction (LVDD), associated with ectopic fat and dysfunctional epicardial adipose tissue (EAT), is emerging as a key research area due to its increasing prevalence and links to metabolic-associated steatotic liver disease (MASLD) and type 2 diabetes mellitus (T2DM). This underscores the importance of early risk assessment and intervention t...

Modeling Diabetes Risk and Progression With Public Health Data: Ontology-Guided, Simulation-Capable Digital Twin Study.

BACKGROUND: Digital twins (DTs) offer a paradigm for health care by enabling data-driven, simulation-capable representations of individual health traj...

[Prevention in Gastroenterology].

Gastroenterology offers a broad, evidence-based range of preventive measures that goes beyond colorectal cancer screening. As a specialty of systemic ...

Artificial Intelligence In The Diagnosis And Prediction Of Breast Cancer-Related Lymphedema: A Scoping Review.

INTRODUCTION: Lymphedema is a chronic complication of breast cancer treatments that can significantly impact the well-being of survivors. This scoping...

Uncoupling toxicity from efficacy in donor selection for allogeneic hematopoietic cell transplantation: a retrospective cohort study using double machine learning.

Haploidentical hematopoietic cell transplantation (HCT) offers potent graft-versus-tumor effects but is historically limited by higher non-relapse mor...

AI-Driven Chemometrics for Multi-omics Data Integration: Advances, Challenges, and Future Directions.

The convergence of artificial intelligence and chemometrics has revolutionized multi-omics data integration, enabling unprecedented insights into comp...

The neutrophil-to-lymphocyte ratio: a psychoneuroimmunological nexus linking depression and cardiovascular comorbidity.

GRaph-based analysis for stroke prediction (GRASP): A multi-modal model for identifying first ischemic stroke in high-risk population using UK biobank.

BACKGROUND: Ischemic stroke accounts for 3.71 million deaths annually worldwide. Yet current risk prediction models demonstrate modest discrimination ...

Multimodal machine learning integrates clinical and comorbidity data to predict breast cancer prognosis and treatment outcomes.

Breast cancer prognosis and treatment outcomes are shaped by intricate interplay between tumor biology, systemic comorbidities, and patient-reported f...

Advancing brain age estimation: normative deviation mapping (NDM) for sensitive detection of pathological aging.

Brain age is a valuable neuroimaging-based biomarker for assessing brain health, typically estimated using machine learning (ML) models. However, ML a...

International consensus on adolescent metabolic health: prevention of obesity and type 2 diabetes.

Use of Machine Learning to Identify Markers of Risk for Fragile X-Associated Tremor/Ataxia Syndrome: A Preliminary Analysis.

OBJECTIVE: The objective of this study was to examine whether machine learning has the capacity to prospectively identify and predict the emergence of...

Integrating Sperm Microscopy, Environmental Exposures, and Lifestyle Factors for Male Fertility Analysis: Protocol for the Nippon Semen and Environmental Exposure Database (N-SEED) Cross-Sectional Study.

BACKGROUND: Conventional semen analysis does not fully capture male reproductive potential. The sperm DNA fragmentation index (DFI) may detect latent ...

Clustering by patients-related characteristics identifies specific phenotypes with different prognosis after resection of non-small cell lung cancer: a French nationwide study from the Epithor database.

INTRODUCTION: Lung cancer remains the leading cause of cancer mortality worldwide despite advances in treatment. Patient-related factors beyond tumour...

Personalizing treatment of pancreatitis-associated chronic pain: the need for an integrated omics approach.

BACKGROUND: Chronic pancreatitis (CP) is a progressive inflammatory disorder characterized by debilitating chronic pain and substantial healthcare bur...

Predictive Model for Mild Autonomous Cortisol Secretion in Patients Evaluated in Artificial Intelligence-Driven Adrenal Incidentaloma Clinic.

BACKGROUND: Mild autonomous cortisol secretion (MACS) is present in approximately 20% to 50% of adrenal incidentalomas. These patients do not exhibit ...

Machine Learning Using Preoperative Patient Factors Can Predict the Severity of Pain Following Primary Total Hip Arthroplasty.

BACKGROUND: Persistent postoperative pain is a challenge in total hip arthroplasty (THA), yet a lack of accurate predictive tools exists for this outc...

Comorbidity Burden and Length of Stay After Myocardial Infarction: A Retrospective Study Using Large Language Model-Assisted Chart Abstraction in a Tertiary Cardiac Hospital.

Patients' length of stay (LOS) during admission for myocardial infarction (MI) represents a closely tracked outcome metric for Cardiology services, wh...

Personalized weight loss management through wearable devices and artificial intelligence.

Early detection of chronic and non-communicable diseases (NCDs) is crucial for effective treatment during the initial stages. This study explores the ...