Background: Emergency/trauma radiology artificial intelligence (AI) is maturing along all stages of technology readiness, with research and development (R&D) ranging from data curation and algorithm development to post-market monitoring and retraining.
Purpose: To develop an expert consensus document on best research practices and methodological priorities for emergency/trauma radiology AI.
Methods: A Delphi consensus exercise was conducted by the ASER AI/ML expert panel between 2022-2024.
This is a case of a 70-year-old female with small bowel evisceration through vaginal cuff dehiscence 14 months after hysterectomy. She presented with a loop of ileum herniated through the vagina. The bowel was irreducible and she was taken to the operating room for exploratory laparotomy, reduction of herniated bowel contents, and repair of vaginal cuff.
View Article and Find Full Text PDFBackground: AI/ML CAD tools can potentially improve outcomes in the high-stakes, high-volume model of trauma radiology. No prior scoping review has been undertaken to comprehensively assess tools in this subspecialty.
Purpose: To map the evolution and current state of trauma radiology CAD tools along key dimensions of technology readiness.
Int J Environ Res Public Health
June 2019
Industrial facilities and other sources can emit air pollutants from fugitive leaks, process malfunctions and area sources that can be difficult to understand and to manage. Next generation emissions measurement (NGEM) approaches executed near facilities are enabling new ways to assess these sources and their impacts to nearby populations. This paper describes complementary uses of emerging NGEM systems in a Louisville, KY industrial district (Rubbertown), focusing on an important area air toxic, 1,3-butadiene.
View Article and Find Full Text PDF