Artificial Intelligence Medical Compendium

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

Showing 291 to 300 of 199,772 articles

Novel Online Platform for Trauma Care-Integrating Trauma Phenotypes to Optimize the Trauma and Injury Severity Score Model: Retrospective Cohort Study.

JMIR medical informatics
BACKGROUND: Severe trauma remains a leading cause of admission to the intensive care unit. The Trauma and Injury Severity Score (TRISS) is an established standard for predicting outcomes and benchmarking the quality of trauma care globally. However, ... read more 

Artificial Intelligence Discontinuation Effects (AI-DICE): An Emerging Phenomenon in Mental Health Applications.

JMIR AI
Artificial intelligence (AI) has emerged as a powerful tool for fostering positive behavior change and enhancing mental health support. However, the abrupt discontinuation or functional degradation of AI-driven interventions, particularly those featu... read more 

Assessing the Accuracy and Reliability of ChatGPT-4 to Answer Clinical EHR Messages in Sports Medicine.

Southern medical journal
OBJECTIVES: Although advancements in electronic health records (EHRs) have improved clinical productivity, digital administrative responsibilities have led to increased physician burnout. With the emergence of large language models (LLMs), their inco... read more 

Evaluating the biological meaning of neural network decisions in EEG-based MCI detection.

Journal of neural engineering
OBJECTIVE: High accuracy in medical classification tasks does not ensure that neural networks reason in ways consistent with clinical or neurobiological understanding. This study examines whether a Vision Transformer (ViT) trained on resting-state EE... read more 

Denoising of low-dose chest computed tomography images using a U-net based convolutional Autoencoder and transfer learning.

Biomedical physics & engineering express
Low-Dose Computed Tomography (LDCT) is a widely used imaging modality to perform CT examinations with a reduced radiation exposure to patients, but it is affected by increased image noise and artifacts with respect to standard dose imaging, which can... read more 

AmygdalaGo-BOLT for boundary-aware segmentation of the human amygdala.

Cell reports methods
Tracing the boundaries of the amygdala from brain images remains a major challenge in human neuroscience. Although large-scale neuroimaging studies increasingly collect thousands of scans to investigate structural development in children and adolesce... read more 

Integrating risk prioritization and interpretable machine learning to inform PFAS management in an urban aquatic system.

Journal of environmental management
Per- and polyfluoroalkyl substances (PFASs) pose persistent challenges to urban environmental management due to their complex sources, ongoing substitution, and contrasting behavior across environmental media. This study assessed the contamination ch... read more 

Investigating heterogeneous human factor effects on crash severity: A counterfactual study in mountainous freeways.

Accident; analysis and prevention
Accurately estimating the causal effect of human factors on crash severity in mountainous freeways is pivotal for developing effective safety strategies. Although previous studies have investigated human factors, they typically focus on estimating av... read more 

The effect of artificial intelligence assisted evidence-based nursing on psychological distress relief and nursing satisfaction of patients with respiratory diseases.

Heart & lung : the journal of critical care
BACKGROUND: Patients with respiratory diseases commonly experience psychological distress. Traditional evidence‑based nursing is limited in personalized and dynamic care. OBJECTIVES: To evaluate whether AI‑assisted evidence‑based nursing reduces psyc... read more 

On-device cough detection and respiratory disease classification enhanced by generative data augmentation.

Computers in biology and medicine
BACKGROUND: Cough sounds are accessible, non-invasive biomarkers for respiratory disease assessment and can be captured using consumer-grade smartphones. Existing approaches typically focus solely on cough detection or rely on server-based deep learn... read more