Technical note: An optimized protocol for standard unenhanced whole-body post-mortem Photon Counting CT imaging.

In recent years, Photon-counting detector CT (PCD CT) has emerged as a new and groundbreaking technology in clinical radiology. While clinical research and practical applications of PCD-CT are constantly evolving, it has not yet been integrated into post-mortem CT (PMCT) imaging. Documented research into the potential applications of PCD CT in the field of post-mortem human forensic pathology and anatomical pathology is scarce in literature.

Upcoding Linked To Up To Two-Thirds Of Growth In Highest-Intensity Hospital Discharges In 5 States, 2011-19.

Diagnosis-based payment systems can create incentives to upcode patients to a higher level of severity to increase payment. In some instances, upcoding can be a form of fraud if providers code patients to a higher complexity than is appropriate, whereas in other instances, upcoding can accurately reflect patient acuity. We estimated the increase in Medicare Severity Diagnosis-Related Group (MS-DRG) upcoding during the period 2011-19, using all-payer discharge-level data from five states.

Artificial intelligence in commercial fracture detection products: a systematic review and meta-analysis of diagnostic test accuracy.

Conventional radiography (CR) is primarily utilized for fracture diagnosis. Artificial intelligence (AI) for CR is a rapidly growing field aimed at enhancing efficiency and increasing diagnostic accuracy. However, the diagnostic performance of commercially available AI fracture detection solutions (CAAI-FDS) for CR in various anatomical regions, their synergy with human assessment, as well as the influence of industry funding on reported accuracy are unknown.

Impact of artificial intelligence assistance on pulmonary nodule detection and localization in chest CT: a comparative study among radiologists of varying experience levels.

The study aimed to evaluate the impact of AI assistance on pulmonary nodule detection rates among radiology residents and senior radiologists, along with assessing the effectiveness of two different commercialy available AI software systems in improving detection rates and LungRADS classification in chest CT. The study cohort included 198 participants with 221 pulmonary nodules. Residents' mean detection rate increased significantly from 64 to 77% with AI assist, while seniors' detection rate remained largely unchanged (85% vs.