Surveys

Evaluating an AI-Enabled Mobile Mental Health Monitoring Tool Among Family Caregivers of Adults Living With Cancer: Single-Arm Feasibility and Acceptability Trial Protocol.

BACKGROUND: Psychological distress, particularly symptoms of depression and anxiety (D&A), is highly prevalent among family caregivers of individuals living with cancer, who often assume central roles in care coordination, treatment adherence, symptom monitoring, and emotional support. Rates of distress among caregivers frequently equal or exceed those observed in patients themselves. Despite incr...

Rapid Generation of Transition-State Conformer Ensembles via Constrained Distance Geometry.

Consideration of transition-state (TS) conformer ensembles is required to accurately model a reaction, and thus plays a key role in computational catalyst design. While CREST and GOAT are established methods for TS conformer ensemble generation, the associated computational cost remains a major bottleneck in computational chemistry pipelines, including for the generation of large machine learning ...

Recurrent neural network long short term memory model to detect the pile toe using raw data of pile integrity test.

This article proposes a novel approach to automatically generate velocity reflectogram of Pile Integrity Testing using a Recurrent Neural Network with...

Ultrasonography-Based Patellar Tendon Area Measurement: Comparability of Automated vs. Manual Segmentation.

While several openly available tools for the automatic segmentation of the anatomical cross-sectional area (ACSA) of muscle exist, there is no open-so...

Evaluating the reliability and guideline concordance of ChatGPT-5 in the management of vascular diseases: a cross-sectional expert-based assessment.

BACKGROUND: Artificial intelligence (AI) tools such as large language models are increasingly used in clinical decision support, yet their reliability...

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...

Physician Perspectives on Web-Based Real-World Statistics for Better-Informed Drug Selection in Epilepsy: Mixed Methods Study.

BACKGROUND: Lately, big data studies have shown promise in using patient characteristics to rank the likelihood of retention of antiseizure medication...

Evaluation of Large Language Models for Peer Review in Transplantation Research: Algorithm Validation Study.

BACKGROUND: Peer review remains central to ensuring research quality, yet it is constrained by reviewer fatigue and human bias. The rapid rise in scie...

Biomedical Data Manifest: A lightweight data documentation mapping to increase transparency for AI/ML.

Biomedical machine learning (ML) models raise critical concerns about embedded assumptions influencing clinical decision-making, necessitating robust ...

The impact of AI anxiety on career decisions of college students.

The rapid advancement of artificial intelligence (AI) has reshaped the employment market, triggering widespread anxiety among college students about t...

Energy diagram: Investigation and application of a design-thinking-driven wind environment simulation tool for sustainable architecture.

Amid climate change and resource constraints, sustainable building design increasingly requires wind-environment optimization to improve energy effici...

Multimodal machine learning models for predicting remission in major depressive disorder using clinical data, blood biomarkers, and DNA methylation.

Major depressive disorder (MDD) is a leading global health burden, yet only one-third of patients achieve remission with initial antidepressant therap...

Learning dynamic binary treatment policies under treatment selection bias: A Conservative Q-Learning approach with representation balancing.

OBJECTIVE: Learn safe, robust dynamic treatment regimes (DTRs) from observational trajectories that exhibit treatment selection bias, using an offline...

Uncertainty-aware machine learning-based prediction of plasma parameters in a microwave atmospheric pressure plasma jet.

Microwave atmospheric pressure plasma jets (MW-APPJs) exhibit significant potential for diverse applications, i.e., hydrogen production, CO2 dissociat...

Artificial Intelligence for Gastroenterology Practice: A Modified Delphi Consensus.

BACKGROUND: The American College of Gastroenterology (ACG) assembled a multidisciplinary task force to evaluate the current state and future direction...

Drug Repositioning by Belief Networks and Ensemble Method.

The approach of drug repositioning, recognized as an efficient strategy to reduce costs and shorten development timelines in the pharmaceutical indust...

Characterising 'Spree Bar': an examination of the popularity, marketing and composition of a vaping device with a nicotine analogue across multiple data streams.

BACKGROUND: Spree Bar, a line of e-cigarette devices introduced in 2023, leverages 6-methylnicotine (6-MN) as its primary ingredient and is available ...

Use of uterine activity to predict preterm birth by artificial intelligence assisted models: a narrative systematic review.

OBJECTIVE: The benefit of interventions to improve neonatal outcomes of preterm birth (PTB) must be balanced with the associated fetal and maternal ri...

Learning fair representation for fine-tuning pre-trained language models.

Pre-trained language models (PLMs) have achieved remarkable success across a wide range of natural language processing tasks, including text classific...

Sparsity and memory constraints interact with training sequence to bias learning of associative maps.

Cognitive maps support inference and planning by representing associations between experiences encoded in memory. These map-like representations are t...