Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 13,231 to 13,240 of 211,153 articles

Professionalism Pulse: Development and Validation of a Natural Language Processing Pipeline and Dashboard for Safety Culture Surveillance in NYC Health + Hospitals

medRxiv
Background: Professionalism and effective communication are foundational determinants of patient safety and quality of care. Unprofessional behaviors frequently serve as active precursors to adverse clinical events. However, proactive organizational ... read more 

Retrospective cohort study extracting coexisting background breast-lesion features from stage I-III invasive breast cancer

medRxiv
Background Background breast features are frequently noted in pathology reports alongside invasive breast cancer but rarely factor into prognosis or treatment decisions. Their relationship to tumor characteristics and patient outcomes remains incompl... read more 

Biomarker Signal Architecture in Cardiovascular Machine Learning: Stability, Redundancy, and Minimal High-Yield Panels After Myocardial Infarction

medRxiv
Background: Machine-learning models based on circulating biomarkers are increasingly used in cardiovascular research; however, model performance alone provides limited insight into how the predictive signal is distributed across features. We aimed to... read more 

Geographical targeting of active case finding for tuberculosis in Pakistan using artificial intelligence software (SPOT-TB): a pragmatic stepped wedge cluster randomized control trial.

medRxiv
Background Community-wide active case-finding (ACF) is being increasingly implemented as a tuberculosis (TB) elimination intervention. However, conventional site selection strategies may result in low yields from screening. We evaluated whether an ar... read more 

Design and Validation of an AI-Assisted Sequential Screening Framework for Psychological Distress in Glaucoma

medRxiv
Purpose: Psychological distress is highly prevalent in glaucoma and is associated with worse adherence, reduced quality of life, and faster disease progression. However, distress is rarely assessed in ophthalmology settings due to time, workflow, and... read more 

Evaluating Large Language Models for Translating Multimodal Phenotype Documentations into Executable EHR Phenotyping Algorithms

medRxiv
Research applications of electronic health record (EHR) phenotypes require translating clinical definitions into executable EHR database queries, a labor-intensive process. We evaluated two frontier large language models across five phenotypes and th... read more 

Predicting Substance Use and Psychotic-Like Experiences in Adolescents

medRxiv
Adolescence is a critical developmental window for the emergence of substance use and psychosis-spectrum symptoms, yet early risk for these outcomes remains poorly understood. Using longitudinal data from the Adolescent Brain Cognitive Development (A... read more 

An Experimental Investigation of the Relationship between AI-Human Workflow Design and Legal Liability for Radiologists: The Erroneous-Change Penalty and Omission Bias

medRxiv
Background: With growing impetus to integrate artificial intelligence (AI) tools into radiology, clinical practices must navigate workflow redesign. This carries implications for medical malpractice liability. Methods: We conducted an online vignette... read more 

Integrated Machine Learning-PanGWAS Reveals Chromosome-Encoded Persistence Networks and Plasmid Plasticity in Recurrent Urinary Tract Infection in Escherichia coli

medRxiv
Background: Recurrent urinary tract infections(rUTI) represent a major clinical challenge due to persistent clinical symptoms, repeated antibiotic exposure, and increased risk of multidrug resistance. Further clinical management of rUTI remains chall... read more 

Machine-Assisted Topic Analysis of Large-Scale Health Experience Data: Identifying Sociodemographic Differences and Evaluating Bias in Large Language Models

medRxiv
Introduction: Large-scale free-text data with socio-demographic information can capture nuanced accounts of lived experience that are difficult to detect in structured measures. However, manual qualitative analysis is difficult to scale, while automa... read more