Primary Care

CellXpress.ai: Machine learning powered system for automation of complex 2D and 3D cell culture workflows.

Attrition in the therapeutic pipeline can often be attributed to a lack of translational efficacy from pre-clinical to clinical phases. Organoids show great promise as a game-changer in disease modeling and drug screening, as they better resemble tissue structure and functionality, and show more predictive responses to drugs. However, challenges associated with the practical adoption of organoids,...

Design and implementation of an end-to-end AI-driven colonoscopy recall workflow at scale.

OBJECTIVES: To develop a large-language-model (LLM)-centric workflow flow extraction and migration of clinician-documented colonoscopy recall recommendations from unstructured reports and letters during an enterprise-wide electronic health record (EHR) transition. MATERIALS AND METHODS: A multi-stage workflow [Optical Character Recognition (OCR) -> LLM -> structured fields] was built around a cent...

Cumulative stress hyperglycemia ratio exposure and dynamic trajectories reveal prognostic determinants of acute hyperlipidemic pancreatitis: an 5-year cohort study.

BACKGROUND: The stress hyperglycemia ratio (SHR) and glycemic variability (GV) both reflect acute glycemic fluctuations, with established roles in car...

Development and validation of a risk prediction model for dysglycaemia at 6-12 weeks postpartum in Chinese women with gestational diabetes: a retrospective cohort study.

BACKGROUND: Compared with normoglycaemic pregnancies, gestational diabetes mellitus (GDM) confers a markedly elevated risk of dysglycaemia at 6-12 wee...

Risk Stratification for Breast Cancer Screening: AJR Expert Panel Narrative Review.

Early detection of breast cancer reduces mortality and is influenced by screening strategies. The balance of benefits and harms within any screening p...

Blood viscosity in clinical practice: A critical review of diagnostic utility, therapeutic implications, and evidence gaps.

Blood viscosity is a key rheological measure that is a biomarker of hematological, cardiovascular, and inflammatory conditions. This systematic review...

Continuous Glucose Monitoring-Derived Metrics and Cardiovascular Risk Among People With Diabetes: Systematic Scoping Review.

BACKGROUND: Conventional clinical markers guide cardiovascular risk stratification; however, continuous glucose monitoring (CGM) data remain absent fr...

High risk score of breast cancer by artificial intelligence (AI) on screening mammograms: a review of negative and cancer cases.

OBJECTIVES: To investigate mammographic features associated with high artificial intelligence (AI) risk scores as provided by two AI models applied to...

Validation of remote multimodal AI screening for Parkinson disease across diverse settings.

BACKGROUND: Timely detection of Parkinson's disease (PD) remains limited by reliance on in-person neurological evaluations that are often costly and g...

Use of Machine-Learning Models to Identify Clinical Features Associated With A Future Clinical Worsening Event in Patients With Pulmonary Arterial Hypertension.

Clinical worsening events are increasingly recognized as a meaningful outcome in pulmonary arterial hypertension (PAH). We applied machine-learning mo...

Automated full-text screening and accelerated reviews using large language models with context-aware agents: an exploratory analysis in biomarker research.

AIMS: Artificial intelligence (AI) tools utilizing large language models (LLMs) can accelerate scientific literature reviews by automating title, abst...

An epidemiological study of Parkinson's disease in Chinese older adults using the Global Burden of Disease and China Health and Retirement Longitudinal Study databases.

INTRODUCTION: The prevalence of Parkinson's disease (PD) has increased globally, especially in China, and emerged as a critical public health challeng...

EDC Profiler: A High-Throughput Screening Server for Identifying Endocrine Disrupting Chemicals toward Multiple Nuclear Receptors.

Endocrine disrupting chemicals (EDCs) are associated with various adverse health outcomes, thus necessitating high-throughput screening. However, curr...

Publisher Correction: Machine Learning Models for Predicting Significant Liver Fibrosis in Patients with Severe Obesity and Nonalcoholic Fatty Liver Disease.

Regional disparities and metabolic determinants of type 2 diabetes in women aged 55 and older.

OBJECTIVE: To assess long-term trends, regional disparities, determinants, and quality of care for type 2 diabetes mellitus (T2DM) among women aged 55...

Prognostic significance of right ventricular myocardial features derived from echocardiography using a deep learning framework in pulmonary arterial hypertension.

BACKGROUND: The function and myocardial characteristics of the right ventricle (RV) are linked to RV dysfunction and prognosis in pulmonary arterial h...

Anxiety and Depression Associated With the Dependent Use of Generative AI in Medical Students: Cross-Sectional Study.

BACKGROUND: The growing integration of artificial intelligence (AI) in higher education has transformed learning processes but also raised concerns ab...

Feasibility and Acceptability of a Prevention-Focused Screener for Perinatal Depression Risk: Mixed Methods Cohort Study.

BACKGROUND: More than 20% of perinatal women experience depression, with suicide being a leading cause of maternal death in the United States. Profess...

Artificial intelligence-assisted peri-operative echocardiography: a multicentre observational study.

INTRODUCTION: Point-of-care transthoracic echocardiography performed by anaesthetists can influence peri-operative management but is constrained by ti...

Topology-preserving, diameter-specific framework for conjunctival vessel segmentation and tortuosity analysis in diabetes.

Diabetes is associated with progressive microvascular remodelling, commonly assessed using retinal imaging, yet alternative non-invasive vascular biom...