Practice Management

Linking cortical structure and delirium in the elderly: insights from cohort study and shared genetic risk analysis.

BACKGROUND: This study aimed to assess the association between regional cortical changes measured via baseline magnetic resonance imaging (MRI) and the incidence of delirium. METHODS: Observational associations were assessed using a prospective cohort from the UK Biobank and an independent clinical cohort. The population-based study included participants aged 60 years or older who had undergone st...

Data integration and systems interoperability: the prerequisite for artificial intelligence in anesthesiology.

PURPOSE OF REVIEW: Anesthesiology generates large volumes of heterogeneous perioperative data, including high-resolution physiological signals, clinical documentation, and device-generated information. Despite this richness, the clinical deployment of artificial intelligence systems remains limited. This review examines how limitations in data integration and systems interoperability constrain the...

Plant genome assembly and annotation.

Plant genome biology is entering a new era defined by fully phased, chromosome-scale, telomere-to-telomere assemblies, enabled by the convergence of l...

Multicentre development and validation of data-driven claims-based algorithms for identifying dermatomyositis and polymyositis in Japan.

OBJECTIVE: To develop and validate data-driven algorithms for identifying patients with dermatomyositis (DM) and polymyositis (PM) using Japanese admi...

Validation of 13 102 International Classification of Diseases, Tenth Revision, Clinical Modification codes using a large language model-based system.

OBJECTIVES: To comprehensively evaluate the validity of International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) co...

Large Language Models for Health Care Text Classification: Systematic Review.

BACKGROUND: Large language models (LLMs) have fundamentally transformed approaches to natural language processing tasks across diverse domains. In hea...

Clinical evaluation of MiADE: a natural language processing system for assisting structured diagnosis recording at the point of care.

OBJECTIVES: To evaluate the usability, usefulness and impact of a novel point of care natural language processing (NLP) system, Medical information AI...

Leveraging AI for Analysis of Digital Health Information on Cancer Prevention Among Arab Youth and Adults: Content Analysis.

BACKGROUND: As TikTok (ByteDance) grows as a major platform for health information, the quality and accuracy of Arabic-language cancer prevention cont...

Improving drug identification in overdose death surveillance by using clinical natural language processing models.

The rising rate of drug-related deaths in the United States, largely driven by fentanyl, requires timely and accurate surveillance. However, critical ...

Learner-Centered Microbiology Teaching via the Flipped Classroom Model: Insights from a Mixed-Methods Educational Study.

CONTEXT: Medical education has evolved to emphasize active learning and technology for competency development. The flipped classroom (FCR) model shift...

StatLLM: A Dataset for Evaluating the Performance of Large Language Models in Statistical Analysis.

The coding capabilities of large language models (LLMs) have opened up new opportunities for automatic statistical analysis in machine learning and da...

Non-coding RNAs as prognostic biomarkers in autoimmune disease.

Autoimmune diseases comprise a broad spectrum of disorders in which both the innate and adaptive branches of the immune system malfunction, mistakenly...

Scaling medical device regulatory science using large language models.

Advances in artificial intelligence (AI) and machine learning (ML) have led to a surge in AI/ML-enabled medical devices, posing new challenges for reg...

Perception of AI Symptom Models in Oncology Nursing: Mixed Methods Evaluation Study.

BACKGROUND: Patients undergoing cancer treatment experience a significant symptom burden. The standard process of symptom management includes patient ...

Transformer-Based Topic Modeling: Characterizing Cannabis Product Adverse Experiences Self-Reported as Requiring Medical Attention on Reddit.

This study uses keyword filtering, a transformer-based algorithm, and inductive content coding to identify and characterize cannabis adverse experienc...

Forensic Transcriptomics: Research Progress of the Past Two Decades.

Over the last two decades, advancements in sequencing technology and data science have significantly deepened the study of transcriptomics, especially...

DNA-Driven EEG monitoring for rapid seizure prediction in healthcare.

BACKGROUND AND OBJECTIVE: Worldwide, over 50 million people suffer from epilepsy, a neurological disorder characterised by recurrent seizures due to a...

Phenotyping of Patients with Age-Related Macular Degeneration Using Artificial Intelligence-Driven Biomarker Patterns in OCT.

PURPOSE: To leverage artificial intelligence-based OCT analysis to classify age-related macular degeneration (AMD) images into distinct subgroups base...

Reduction of motion artifacts from photoplethysmography signals using learned convolutional sparse coding.

Objective.Wearable devices with embedded photoplethysmography (PPG) enable continuous non-invasive monitoring of cardiac activity, offering a promisin...

Health sciences students' attitudes toward artificial intelligence: predictors of ethical awareness, clinical decision-making, and public health perceptions-a cross-sectional study.

This study investigates health sciences students' attitudes toward artificial intelligence (AI) and the implications for ethical awareness, clinical d...