Emergency Medicine

Establishing methodological standards for the development of artificial intelligence-based Clinical Decision Support in emergency medicine.

OBJECTIVE: Artificial intelligence (AI) offers opportunities for managing the complexities of clinical care in the emergency department (ED), and Clinical Decision Support has been identified as a priority application. However, there is a lack of published guidance on how to rigorously develop and evaluate these tools. We sought to answer the question, "What methodological standards should be appl...

Chemical Space Networks Enhance Toxicity Recognition via Graph Embedding.

Chemical space networks (CSNs) are a new effective strategy for detecting latent chemical patterns irrespective of defined coordinate systems based on molecular descriptors and fingerprints. CSNs can be a new powerful option as a new approach method and increase the capacity of assessing potential adverse impacts of chemicals on human health. Here, CSNs are shown to effectively characterize the to...

Mapping and Summarizing the Research on AI Systems for Automating Medical History Taking and Triage: Scoping Review.

BACKGROUND: The integration of artificial intelligence (AI) systems for automating medical history taking and triage can significantly enhance patient...

Integrating manual annotation with deep transfer learning and radiomics for vertebral fracture analysis.

BACKGROUND: Vertebral compression fractures (VCFs) are prevalent in the elderly, often caused by osteoporosis or trauma. Differentiating acute from ch...

Deep learning: A game changer in drug design and development.

The lengthy and costly drug discovery process is transformed by deep learning, a subfield of artificial intelligence. Deep learning technologies exped...

CGNet: Few-shot learning for Intracranial Hemorrhage Segmentation.

In recent years, with the increasing attention from researchers towards medical imaging, deep learning-based image segmentation techniques have become...

Deep Learning-Enhanced Chemiluminescence Vertical Flow Assay for High-Sensitivity Cardiac Troponin I Testing.

Democratizing biomarker testing at the point-of-care requires innovations that match laboratory-grade sensitivity and precision in an accessible forma...

Artificial intelligence-based clinical decision support in the emergency department: A scoping review.

OBJECTIVE: Artificial intelligence (AI)-based clinical decision support (CDS) has the potential to augment high-stakes clinical decisions in the emerg...

Machine Learning-Based CT Radiomics Model to Predict the Risk of Hip Fragility Fracture.

RATIONALE AND OBJECTIVES: This research aimed to develop a combined model based on proximal femur attenuation values and radiomics features at routine...

Machine Learning-Enabled Drug-Induced Toxicity Prediction.

Unexpected toxicity has become a significant obstacle to drug candidate development, accounting for 30% of drug discovery failures. Traditional toxici...

Bioinspired Super-Robust Conductive Hydrogels for Machine Learning-Assisted Tactile Perception System.

Conductive hydrogels have attracted significant attention due to exceptional flexibility, electrochemical property, and biocompatibility. However, the...

Prediction of the Risk of Adverse Clinical Outcomes with Machine Learning Techniques in Patients with Noncommunicable Diseases.

Decision-making in chronic diseases guided by clinical decision support systems that use models including multiple variables based on artificial intel...

Conventional and machine learning-based analysis of age, body weight and body height significance in knot position-related thyrohyoid and cervical spine fractures in suicidal hangings.

The thyrohyoid complex and cervical spine fracture distribution patterns may reflect the knot position as the force distribution by the noose to diffe...

A comparative analysis of trauma-related mortality in South Korea using classification models.

BACKGROUND: Reducing mortality among severe trauma patients requires the establishment of an effective emergency transportation system and the rapid t...

Deep learning for automated hip fracture detection and classification : achieving superior accuracy.

AIMS: The aim of this study was to develop and evaluate a deep learning-based model for classification of hip fractures to enhance diagnostic accuracy...

Synergistic modeling of hemorrhagic dengue fever: Passive immunity dynamics and time-delay neural network analysis.

Dengue fever poses a formidable epidemiological challenge, particularly for vulnerable groups such as infants. This research paper establishes a mathe...

Advancing newborn care: Precise time of birth detection using ai-driven thermal imaging with adaptive normalization.

Around 5%-10% of newborns need assistance to start breathing. Currently, there is a lack of evidence-based research, objective data collection, and op...

Human-centred AI for emergency cardiac care: Evaluating RAPIDx AI with PROLIFERATE_AI.

BACKGROUND: Chest pain diagnosis in emergency care is hindered by overlapping cardiac and non-cardiac symptoms, causing diagnostic uncertainty. Artifi...

A pediatric emergency prediction model using natural language process in the pediatric emergency department.

This study developed a predictive model using deep learning (DL) and natural language processing (NLP) to identify emergency cases in pediatric emerge...

Marigold: a machine learning-based web app for zebrafish pose tracking.

BACKGROUND: High-throughput behavioral analysis is important for drug discovery, toxicological studies, and the modeling of neurological disorders suc...