Emergency Medicine

DeepADR: Multi-modal Prediction of Adverse Drug Reaction Frequency by Integrating Early-Stage Drug Discovery Information via Kolmogorov-Arnold Networks

Adverse drug reactions (ADRs) are a major cause of clinical trial failure and post-market withdrawal, posing significant risks to public health and impeding drug development. While computational methods offer an alternative to costly preclinical testing, existing models often fail with novel compounds by requiring pre-existing information such as drug-ADR associations or by inadequately integratin...

AOP Net: An AI-Enhanced Software Platform for the Visualization and Analysis of Complex Toxicological Pathways

The Adverse Outcome Pathway (AOP) framework is a cornerstone of 21st-century toxicology, providing a structured method for organizing mechanistic knowledge to support risk assessment. However, the inherent complexity of biological systems, characterized by interconnected signaling networks, reveals the limitations of simple, linear AOP representations. This has created a pressing need for advanced...

A unified derivative-like dopaminergic computation across valences

Dopamine activity in the brain affects decision-making and adaptive behaviors. A wealth of studies indicate that dopamine activity encodes discrepancy...

A Machine Learning Approach to Predicting Dyspnea with Noninvasive Biomarkers

Dyspnea is the subjective sensation of breathing discomfort. This symptom is highly prevalent in patients with chronic and critical illness, and its p...

STARNet enables spatially resolved inference of gene regulatory networks from spatial multi-omics data

Biological tissues are composed of distinct microenvironments that spatially orchestrate gene expression and cell identity. However, the regulatory pr...

Adaptive Feature-Weighted Stacking Ensemble for Short-Term Risk Prediction of Prolonged Length of Stay in Elderly Trauma Patients

The Adaptive Feature-Weighted Stacking Ensemble (AFWSE) model is presented here as a new machine learning method that provides staged prediction of pr...

High-throughput multi-camera array microscope platform for automated 3D behavioral analysis of swimming zebrafish larvae

Understanding the behavioral and morphological dynamics of moving model organisms like the zebrafish larvae requires accurate, high-throughput 3D anal...

Mechanical stretch disrupts calcium dynamics and redistributes Piezo1 in human astrocytes

Astrocytes regulate the activity of nearby neurons so disruption of astrocyte calcium dynamics by traumatic brain injury (TBI) could have profound con...

Systematic Review of Artificial Intelligence use in behavioral analysis of invertebrate and larval model organisms: Methods, Applications and Future Recommendations

Invertebrate and larval model organisms such as Drosophila melanogaster, Caenorhabditis elegans, Danio rerio larvae, and Galleria mellonella are incre...

Automated spermatogenic staging in PAS-stained testes of Sprague-Dawley rats using a deep learning model for normal and atrophied tissues

The spermatogenic stage serves as a vital criterion for assessing normal spermatogenesis and is central to evaluating reproductive toxicity. Current m...

Predicting Toxicity and Bioactivity of the Chemical Exposome: A Case Study for the Blood Exposome Database

Humans are exposed to thousands of chemicals throughout their life. Many of these chemicals are detected in blood and have been catalogued in the Bloo...

Dorsolateral striatal acetylcholine reorganizes neural ensembles to anticipate threat

Adaptive behavior requires flexible encoding of emotional valence. Although striatal acetylcholine (ACh) signaling is critical for reinforcement learn...

Integration of artificial intelligence and high-content screening enabled identification of drugs for long-term treatment of cerebral cavernous malformation disease

Adults and children with cerebral cavernous malformations (CCMs) are at risk of experiencing lifelong complications such as hemorrhagic strokes, neuro...

Modeling trajectories of routine blood tests as dynamic biomarkers for outcome in spinal cord injury

Early outcome prediction after acute traumatic spinal cord injury (SCI) is challenging due to pathological complexities and population heterogeneity. ...

Potential of ChatGPT in Youth Mental Health Emergency Triage: Comparative Analysis with Clinicians

Large language models (LLMs), such as GPT-4, are increasingly integrated into healthcare to support clinicians in making informed decisions. Given Cha...

Automated Segmentation of Trunk Musculature with a Deep CNN Trained from Sparse Annotations in Radiation Therapy Patients with Metastatic Spine Disease

Given the high prevalence of vertebral fractures post-radiotherapy in patients with metastatic spine disease, accurate and rapid muscle segmentation c...

Systemic Metabolic Alterations after Aneurysmal Subarachnoid Hemorrhage: A Plasma Metabolomics Approach

Aneurysmal subarachnoid hemorrhage (aSAH) causes systemic changes that contribute to delayed cerebral ischemia (DCI) and morbidity. Circulating metabo...

ICU Readmission Prediction for Intracerebral Hemorrhage Patients using MIMIC III and MIMIC IV Databases

Intracerebral hemorrhage (ICH) is a critical form of stroke resulting from bleeding within the brain, with a mortality rate of 40-50% within a few day...

Machine Learning-Based Prediction of ICU Readmissions in Intracerebral Hemorrhage Patients: Insights from the MIMIC Databases

Intracerebral hemorrhage (ICH) is a life-risking condition characterized by bleeding within the brain parenchyma. ICU readmission in ICH patients is a...

Trust in large language model-based solutions in healthcare among people with and without diabetes: a cross-sectional survey from the Health in Central Denmark cohort

Large language models have gained significant public awareness since ChatGPT’s release in 2022. This study describes the perception of chatbot-assiste...