RATIONALE AND OBJECTIVES: Effective trauma care in emergency departments necessitates rapid diagnosis by interdisciplinary teams using various medical data. This study constructed a multimodal diagnostic model for abdominal trauma using deep learning...
Journal of the American College of Surgeons
30639299
BACKGROUND: In an earlier study, we reported the successful reduction in the use of damage control laparotomy (DCL); however, no change in the relative frequencies of specific indications was observed. In this study, we aimed to use machine learning ...
The journal of trauma and acute care surgery
32569105
BACKGROUND: Computed tomography is the criterion standard for diagnosing intra-abdominal injury (IAI) but is expensive and risks radiation exposure. The Pediatric Emergency Care Applied Research Network (PECARN) model identifies children at low risk ...
International journal of surgery (London, England)
36999810
BACKGROUND: Splenic injury is the most common solid visceral injury in blunt abdominal trauma, and high-resolution abdominal computed tomography (CT) can adequately detect the injury. However, these lethal injuries sometimes have been overlooked in c...
Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
38189316
BACKGROUND: Multi-detector contrast-enhanced abdominal computed tomography (CT) allows for the accurate detection and classification of traumatic splenic injuries, leading to improved patient management. Their effective use requires rapid study inter...
Journal of imaging informatics in medicine
38366294
Computed tomography (CT) is the most commonly used diagnostic modality for blunt abdominal trauma (BAT), significantly influencing management approaches. Deep learning models (DLMs) have shown great promise in enhancing various aspects of clinical pr...
World journal of emergency surgery : WJES
38711150
BACKGROUND: Abdominal computed tomography (CT) scan is a crucial imaging modality for creating cross-sectional images of the abdominal area, particularly in cases of abdominal trauma, which is commonly encountered in traumatic injuries. However, inte...
BACKGROUND: This study aimed to use natural language processing to predict the presence of intra-abdominal injury using unstructured data from electronic medical records.
The journal of trauma and acute care surgery
39327643
BACKGROUND: Current tools to review focused abdominal sonography for trauma (FAST) images for quality have poorly defined grading criteria or are developed to grade the skills of the sonographer and not the examination. The purpose of this study is t...
Purpose To evaluate the performance of the winning machine learning models from the 2023 RSNA Abdominal Trauma Detection AI Challenge. Materials and Methods The competition was hosted on Kaggle and took place between July 26 and October 15, 2023. The...