Obesity

Generation of Synthetic Data in Health Surveys Using Large Language Models

Background: Generating synthetic data using artificial intelligence, such as large language models (LLMs), is a useful strategy in public health because it can reduce time and costs, expand access to data, and facilitate information sharing without compromising confidentiality. Objective: To evaluate the consistency and psychometric plausibility of synthetic data generated by an LLM to simulate th...

SCOPE-PD: Explainable AI on Subjective and Clinical Objective Measurements of Parkinson's Disease for Precision Decision-Making

Parkinson's disease (PD) is a chronic and complex neurodegenerative disorder influenced by genetic, clinical, and lifestyle factors. Predicting this disease early is challenging because it depends on traditional diagnostic methods that face issues of subjectivity, which commonly delay diagnosis. Several objective analyses are currently in practice to help overcome the challenges of subjectivity; h...

Clinical and Cross-Domain Validation of an LLM-Guided, Literature-Based Gene Prioritization Framework

Background: We previously published a literature based pipeline for sepsis gene prioritization (PS3 and candidate genes) using an LLM enabled retrieva...

Using Natural Language Processing of Clinical Notes to Supplement Structured Electronic Health Record Data for Phenotyping Smoking and Obesity in a Healthcare System

Purpose: Studies based on electronic health records (EHR) often rely on structured data, which may incompletely capture important clinical phenotypes ...

Refining cardiometabolic risk assessment using MRI-derived pancreas volume and fat content: insights from the NAKO and UK Biobank

BackgroundThe pancreas is essential for metabolic homeostasis. Alterations in morphology and parenchymal integrity may impact proper function but are ...

Leveraging Explainable Temporal-Modelling Machine Learning to Identify Distinct Multimorbidity Trajectory Profiles in Acute Myocardial Infarction

IntroductionAcute myocardial infarction (AMI) remains a leading cause of mortality, with the coexistence of other conditions (i.e., multimorbidity) co...

Predicting Body Composition from Chest Radiographs by Deep Learning: 10-year Mortality and Geriatric Outcomes

BackgroundBody composition strongly influences clinical outcomes in older adults, yet body mass index (BMI) lacks discriminatory power, and standard t...

Histological aging signatures enable tissue-specific disease prediction from blood

Aging, the leading risk factor for numerous diseases, manifests through diverse structural and architectural changes in human tissues, providing an op...

Nutritional and lifestyle predictors of rectal bleeding in functional constipation: A machine learning approach.

BACKGROUND: Rectal bleeding among young adults is an increasingly common clinical concern often linked with chronic constipation and unhealthy lifesty...

Improving image quality and diagnostic performance using deep learning image reconstruction in 100-kVp CT enterography for patients with wide-range body mass index.

OBJECTIVE: To assess the clinical value of the deep learning image reconstruction (DLIR) algorithm compared with conventional adaptive statistical ite...

Novel composite health assessment risk model for older allogeneic transplant recipients: BMT-CTN 1704.

Allogeneic hematopoietic cell transplantation (allo-HCT) is potentially curative for older adults with hematologic malignancies. Concerns on nonrelaps...

EVALUATION OF PROGNOSTIC RISK MODELS BASED ON AGE AND COMORBIDITY IN SEPTIC PATIENTS: INSIGHTS FROM MACHINE LEARNING AND TRADITIONAL METHODS IN A LARGE-SCALE, MULTICENTER, RETROSPECTIVE STUDY.

Background: Age and comorbidity significantly impact the prognosis of septic patients and inform treatment decisions. To provide clinicians with effec...

Radiation and contrast dose reduction in coronary CT angiography for slender patients with 70 kV tube voltage and deep learning image reconstruction.

OBJECTIVE: To evaluate the radiation and contrast dose reduction potential of combining 70 kV with deep learning image reconstruction (DLIR) in corona...

Deep Learning Reveals Liver MRI Features Associated With PNPLA3 I148M in Steatotic Liver Disease.

BACKGROUND: Steatotic liver disease (SLD) is the most common liver disease worldwide, affecting 30% of the global population. It is strongly associate...

Automated segmentation of target volumes in breast cancer radiotherapy, impact on target size and dose to organs at risk.

INTRODUCTION: Target volume delineation is crucial in breast cancer radiotherapy planning but involves significant interobserver variability. Deep lea...

A lightweight graph neural network to predict long-term mortality in coronary artery disease patients: an interpretable causality-aware approach.

BACKGROUND: Coronary artery disease (CAD) causes substantial death toll in the United States and worldwide. While traditional methods for CAD mortalit...

Development and validation of an interpretable machine learning model for predicting hyperuricemia risk: Based on environmental chemical exposure.

Hyperuricemia is a global health concern, with environmental chemicals as risk factors. This study used data of multiple environmental chemical exposu...

From classical approaches to artificial intelligence, old and new tools for PDAC risk stratification and prediction.

Pancreatic ductal adenocarcinoma (PDAC) is recognized as one of the most lethal malignancies, characterized by late-stage diagnosis and limited therap...

Comparing logistic regression and machine learning for obesity risk prediction: A systematic review and meta-analysis.

BACKGROUND: Logistic regression (LR) has traditionally been the standard method used for predicting binary health outcomes; however, machine learning ...

Hugan Tiaoshen Formula Improves the Comorbid Mechanism of Schizophrenia and Sleep Disorder via Multitarget Interaction Network.

This study aims to integrate cross-disease omics data and perform multidimensional analysis to uncover the molecular basis of schizophrenia (SCZ) and ...