Latest AI and machine learning research in emergency medicine for healthcare professionals.
UNLABELLED: The escalating therapeutic use of methadone has coincided with an increase in accidental...
The detection and identification of polycyclic aromatic hydrocarbons (PAHs) and their derivatives, p...
Acute respiratory distress syndrome (ARDS) is a severe organ dysfunction associated with significant...
OBJECTIVE: Artificial intelligence (AI) offers opportunities for managing the complexities of clinic...
Chemical space networks (CSNs) are a new effective strategy for detecting latent chemical patterns i...
BACKGROUND: The integration of artificial intelligence (AI) systems for automating medical history t...
BACKGROUND: Vertebral compression fractures (VCFs) are prevalent in the elderly, often caused by ost...
The lengthy and costly drug discovery process is transformed by deep learning, a subfield of artific...
In recent years, with the increasing attention from researchers towards medical imaging, deep learni...
Democratizing biomarker testing at the point-of-care requires innovations that match laboratory-grad...
OBJECTIVE: Artificial intelligence (AI)-based clinical decision support (CDS) has the potential to a...
RATIONALE AND OBJECTIVES: This research aimed to develop a combined model based on proximal femur at...
Unexpected toxicity has become a significant obstacle to drug candidate development, accounting for ...
Decision-making in chronic diseases guided by clinical decision support systems that use models incl...
The thyrohyoid complex and cervical spine fracture distribution patterns may reflect the knot positi...
BACKGROUND: Reducing mortality among severe trauma patients requires the establishment of an effecti...
Dengue fever poses a formidable epidemiological challenge, particularly for vulnerable groups such a...
Around 5%-10% of newborns need assistance to start breathing. Currently, there is a lack of evidence...
BACKGROUND: Chest pain diagnosis in emergency care is hindered by overlapping cardiac and non-cardia...
This study developed a predictive model using deep learning (DL) and natural language processing (NL...
BACKGROUND: High-throughput behavioral analysis is important for drug discovery, toxicological studi...