Obesity

Artificial Intelligence Across the Obesity Continuum: From Mechanistic Insights to Global Precision Prevention and Therapy.

Obesity is a complex, rapidly escalating global health challenge that demands innovation across biology, clinical care, and public health. This review synthesizes evidence on artificial intelligence (AI) revolutionizing obesity research and management. In mechanistic discovery, AI techniques like deep neural networks and graph architectures integrate multi-omics, microbiome, and wearable-sensor da...

Predictors of glycemic control with imeglimin for type 2 diabetes: Results of machine learning analyses using clinical trial data.

INTRODUCTION: Identifying patient characteristics predictive of treatment response is crucial for optimizing type 2 diabetes outcomes. Using data from three phase 2/3 imeglimin trials in Japan, this analysis applied machine learning to determine characteristics associated with HbA1c improvement. METHODS: Regression tree and random forest methods identified baseline characteristics predictive of Hb...

Sex-specific cardiovascular risk prediction using AI-derived epicardial adipose tissue measurements on CT calcium scoring exams.

BACKGROUND: The Agatston CAC score from CT-calcium scoring (CTCS) is a standard guideline recommended measure for cardiovascular risk assessment that ...

AlzStack: Forecasting early-onset Alzheimer's with an explainable AI system using multiple data balancing techniques.

Alzheimer's disease (AD) is a degenerative neurological disease that progresses over time, making early detection crucial for effective intervention a...

Prediction of Postherpetic Neuralgia in Patients with Acute and Subacute Herpetic Neuralgia Using Structural Magnetic Resonance Imaging: A Retrospective Study.

INTRODUCTION: This study integrated structural magnetic resonance imaging (sMRI) of the brain with clinical characteristics to identify the "vulnerabl...

Enlarged Perivascular Spaces and Modifiable Vascular Risk Factors: Cross-Sectional and Longitudinal Analysis in the UK Biobank Cohort.

OBJECTIVE: To examine cross-sectional and longitudinal associations between vascular risk factors, APOE genotype, and perivascular spaces (PVS), with ...

Artificial intelligence-enabled electrocardiographic sex discordance and the risk of incident atrial fibrillation: A multinational cohort study.

BACKGROUND: Binary classification of sex fails to capture the sex-related continuum of atrial fibrillation (AF) risk. OBJECTIVE: This study aimed to d...

The global epidemiology of acute myeloid leukaemia.

Acute myeloid leukaemia (AML) is an aggressive haematological malignancy with an incidence that increases with age and varies widely across regions ow...

Developing and Validating a Prediction Model for the Severe Pain-Fatigue-Sleep Disturbance Symptom Cluster in Patients with Lung Cancer Following Chemotherapy: A Machine Learning Analysis.

OBJECTIVES: Pain-fatigue-sleep disturbance symptom (PFS) cluster is the most common symptom cluster in patients with lung cancer following chemotherap...

Pharmacoepidemiologic characterization of cannabis use and symptomatology in rheumatology using natural language processing of electronic health record clinic notes.

Up to 70% of patients with autoimmune rheumatic diseases (ARDs), including rheumatoid arthritis, psoriatic arthritis, and systemic lupus erythematosus...

How do Artificial Intelligence chatbots respond to questions from adolescent personas about their eating, body weight or appearance?

BACKGROUND: Body image and eating behaviours are common areas of concern for early adolescents. Artificial Intelligence (AI) interactions are becoming...

Digital health integration in chronic kidney disease.

Chronic kidney disease (CKD) is a growing global health burden characterized by progressive renal dysfunction, high comorbidity rates, and substantial...

Applications of artificial intelligence-based conversational agents in healthcare: A systematic umbrella review.

BACKGROUND: Artificial intelligence-based conversational agents (AI-based CAs) have emerged as essential tools for communication and service delivery ...

The "A-B-C" Classification Reveals Outcome Trajectories in Patients With Hepatocellular Carcinoma Under Atezolizumab/Bevacizumab.

BACKGROUND & AIMS: We aimed to identify subgroups of patients with unresectable hepatocellular carcinoma (HCC) using a non a priori, data-driven machi...

Explainable machine learning-based prediction of psoriatic arthritis flares using heterogenous real-world data for personalised patient care.

Psoriatic arthritis (PsA) is a chronic inflammatory disease characterised by unpredictable flare-ups that are difficult to forecast, particularly in p...

Cancer as a main contributor to multimorbidity in the UK Biobank: analysis of risk factors using conventional statistical modelling and machine learning.

Cancer frequently co-occurs with other chronic conditions, contributing substantially to disease burden. Multimorbidity is an increasing public health...

Total-body [18F]FDG-PET/CT imaging of healthy volunteers with minimal effective dose.

PURPOSE: High-sensitivity, total-body (TB) positron emission tomography (PET) and computed tomography (CT) imaging systems enable substantial reductio...

Diverse combination of factors associated with the development of diabetic kidney disease among data-driven diabetes subtypes: analysis of the J-DREAMS registry.

AIMS/HYPOTHESIS: Available methods for predicting the onset and progression of diabetic kidney disease (DKD) and end-stage kidney disease (ESKD) are n...

An explainable machine learning model for comorbidity risk stratification in patients with fractures admitted to the intensive care unit: a multicenter study.

BACKGROUND: Among traumatic-fracture patients admitted to intensive care units (ICUs), those with substantial chronic comorbidities recover more slowl...

Development of explainable machine learning-based prediction models of depression with mild and severe insomnia in middle-aged and elderly Chinese people.

BACKGROUND: The risk of depression is significantly elevated in middle-aged and older adults with insomnia; however, the pathways between mild and sev...