Introduction: The aim of this study was to first evaluate the quality of studies investigating the diagnostic accuracy of radiographers as mammogram screen-readers and then to develop an adapted tool for determining the quality of screen-reading studies.
Methods: A literature search was used to identify relevant studies and a quality evaluation tool constructed by combining the criteria for quality of Whiting, Rutjes, Dinnes et al. and Brealey and Westwood. This constructed tool was then applied to the studies and subsequently adapted specifically for use in evaluating quality in studies investigating diagnostic accuracy of screen-readers.
Results: Eleven studies were identified and the constructed tool applied to evaluate quality. This evaluation resulted in the identification of quality issues with the studies such as potential for bias, applicability of results, study conduct, reporting of the study and observer characteristics. An assessment of the applicability and relevance of the tool for this area of research resulted in adaptations to the criteria and the development of a tool specifically for evaluating diagnostic accuracy in screen-reading.
Conclusions: This tool, with further refinement and rigorous validation can make a significant contribution to promoting well-designed studies in this important area of research and practice.
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http://dx.doi.org/10.1002/jmrs.68 | DOI Listing |
Sci Rep
December 2024
School of Chemistry, Faculty of Engineering and Physical Sciences, University of Southampton, Life Sciences Building 85, University Road, Highfield, Southampton, SO17 1BJ, UK.
Osteoarthritis (OA) is a complex disease of cartilage characterised by joint pain, functional limitation, and reduced quality of life with affected joint movement leading to pain and limited mobility. Current methods to diagnose OA are predominantly limited to X-ray, MRI and invasive joint fluid analysis, all of which lack chemical or molecular specificity and are limited to detection of the disease at later stages. A rapid minimally invasive and non-destructive approach to disease diagnosis is a critical unmet need.
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December 2024
Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000, Fujian, China.
The monocyte-to-Apolipoprotein A1 ratio (MAR) emerges as a potentially valuable inflammatory biomarker indicative of metabolic dysfunction-associated fatty liver disease (MASLD). Accordingly, this investigation primarily aims to assess the correlation between MAR and MASLD risk. A cohort comprising 957 individuals diagnosed with type 2 diabetes mellitus (T2DM) participated in this study.
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December 2024
Department of Artificial Intelligence Convergence, Chonnam National University, Gwangju, 61186, Republic of Korea.
Polarization-sensitive optical coherence tomography (PS-OCT) measures the polarization state of backscattered light from tissues and provides valuable insights into the birefringence properties of biological tissues. Contrastive unpaired translation (CUT) was used in this study to generate a synthetic PS-OCT image from a single OCT image. The challenges related to extensive data requirements relying on labeled datasets using only pixel-wise correlations that make it difficult to efficiently regenerate the periodic patterns observed in PS-OCT images were addressed.
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December 2024
Artificial Intelligence in Medical Sciences Research Center, Smart University of Medical Sciences, Tehran, Iran.
Failure to predict stroke promptly may lead to delayed treatment, causing severe consequences like permanent neurological damage or death. Early detection using deep learning (DL) and machine learning (ML) models can enhance patient outcomes and mitigate the long-term effects of strokes. The aim of this study is to compare these models, exploring their efficacy in predicting stroke.
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December 2024
Department of General Surgery, Cancer center, Division of Hepatobiliary and Pancreatic Surgery, Affiliated People's Hospital, Zhejiang Provincial People's Hospital, Hangzhou Medical College, 310014, Hangzhou, Zhejiang Province, China.
Despite the growing adoption of laparoscopic hepatectomy (LH) for intrahepatic cholangiocarcinoma (ICC), there is no scoring system available designed to evaluate its surgical complexity. This paper aims to introduce a novel difficulty scoring system (DSS), designated as the Wei-DSS, exclusively tailored to assess the surgical difficulty of pure LH for ICC. We retrospectively collected clinical data from ICC patients who underwent pure LH at our institution, spanning from November 2018 to May 2024.
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