Here we describe the development and evaluation of a survey instrument to assess the research suitability of veterinary electronic medical records (EMRs) through the conduct of two studies as part of the Dog Aging Project (DAP). In study 1, four reviewers used the instrument to score a total of 218 records in an overlapping matrix of pairs to assess inter-rater agreement with respect to appropriate format (qualification), identification match (verification), and record quality. Based upon the moderate inter-rater agreement with respect to verification and the relatively large number of records that were incorrectly rejected the instrument was modified and more specific instructions were provided. In study 2, a modified instrument was again completed by four reviewers to score 100 different EMRs. The survey scores were compared to a gold standard of board-certified specialist review to determine receiver operating curve statistics. The refined survey had substantial inter-rater agreement across most qualification and verification questions. The cut-off value identified had a sensitivity of 95 and 96% (by reviewer 1 and reviewer 2, respectively) and a specificity of 82% and 91% (by reviewer 1 and reviewer 2, respectively) to predict gold standard acceptance or rejection of the record. Using just qualification and verification questions within the instrument (as opposed to full scoring) minimally impacted sensitivity and specificity and resulted in substantial time savings in the review process.
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http://dx.doi.org/10.3389/fvets.2022.941036 | DOI Listing |
Insights Imaging
January 2025
Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy.
Objectives: This article aims to evaluate the use and effects of an artificial intelligence system supporting a critical diagnostic task during radiology resident training, addressing a research gap in this field.
Materials And Methods: We involved eight residents evaluating 150 CXRs in three scenarios: no AI, on-demand AI, and integrated-AI. The considered task was the assessment of a multi-regional severity score of lung compromise in patients affected by COVID-19.
Eur Spine J
January 2025
Department of Spine Surgery, The Third Hospital of Hebei Medical University, 139 Ziqiang Road, Shijiazhuang, 050051, China.
Objective: Spinopelvic sagittal balance ensures efficient posture and minimizes energy expenditure by aligning the spine, pelvis, and lower extremities. Deviations can cause clinical issues like back pain and functional limitations. Key radiographic parameters, including pelvic tilt (PT), pelvic incidence (PI), sacral slope (SS), and lumbar lordosis (LL), are essential for evaluating spinal pathologies and planning surgeries.
View Article and Find Full Text PDFJ Vet Diagn Invest
January 2025
Åkerblå, Sistranda, Norway.
Compromised gill health is a critical cause of forfeited welfare in Atlantic salmon farming. Detecting and quantifying the early onset of gill disease is important to reveal initial inflicting stimuli. We collected gill samples of 45 Atlantic salmon from 2 commercial recirculating aquaculture systems (RASs) spanning fry-to-market-size fish with no clinical signs of gill disease.
View Article and Find Full Text PDFEur Radiol
January 2025
Department of Radiology, University of Washington, Seattle, WA, USA.
Objective: To investigate the predictive value of tumor iodine concentration obtained with dual-energy CT (DECT) for treatment response in patients treated with immune checkpoint inhibitors (ICI).
Materials And Methods: Retrospective single-center study of consecutive metastatic melanoma and renal cell carcinoma (RCC) patients undergoing first-line ICI treatment. The iodine concentration measurement time points include prior to initiation of therapy (baseline [BL]), after initiation (follow-up [FU1]), and either time point nearest to 12 months or at time of progression (final follow-up [FFU]).
Int J Gen Med
January 2025
School of Biomedical Engineering & State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, People's Republic of China.
Purpose: Conventional brain MRI protocols are time-consuming, which can lead to patient discomfort and inefficiency in clinical settings. This study aims to assess the feasibility of using artificial intelligence-assisted compressed sensing (ACS) to reduce brain MRI scan time while maintaining image quality and diagnostic accuracy compared to a conventional imaging protocol.
Patients And Methods: Seventy patients from the department of neurology underwent brain MRI scans using both conventional and ACS protocols, including axial and sagittal T2-weighted fast spin-echo sequences and T2-fluid attenuated inversion recovery (FLAIR) sequence.
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