Expert Perspective: Diagnosis and Treatment of Castleman Disease
Arthritis &Rheumatology, Accepted Article.Summary Castleman disease (CD) is a major diagnostic challenge for Rheumatologists. Unicentric CD (UCD) involves one enlarged lymph node region whereas multicentric CD (MCD) involves multiple enlarged lymph node regions. Both UCD and MCD may exhibit a wide range of symptoms that overlap with other immune‐mediated conditions.
Luke Y.C. Chen +2 more
wiley +1 more source
Using artificial intelligence to detect chest X-rays with no significant findings in a primary health care setting in Oulu, Finland [PDF]
arXiv, 2022 Objectives: To assess the use of artificial intelligence-based software in ruling out chest X-ray cases, with no significant findings in a primary health care setting. Methods: In this retrospective study, a commercially available artificial intelligence (AI) software was used to analyse 10 000 chest X-rays of Finnish primary health care patients. In
arxiv
Diagnostic value of medical thoracoscopy in malignant pleural effusion
BMC Pulmonary Medicine, 2017 BackgroundMedical thoracoscopy has been shown to be an efficacious procedure in diagnosing unexplained exudative pleural effusions with excellent safety. This study aimed to assess the diagnostic significance of thoracoscopy in the management of patients
Yan-bing Wu +6 more
semanticscholar +1 more source
Egyptian Journal of Chest Disease and Tuberculosis, 2013 Background: The discrimination of pleural thickening from minimal pleural effusion may be difficult as both lesions appear as anechoic on grayscale ultrasound, hence, free of “echoes” does not confirm the presence of pleural fluid.
Ali A. Hasan +2 more
doaj +1 more source
Will pleural fluid affect surface wave speed measurements of the lung using lung ultrasound surface wave elastography: experimental and numerical studies on sponge phantom? [PDF]
arXiv, 2018 Pleural effusion manifested as compression of pleural fluid on the lung parenchyma, contributing to hypoxemia. Medical procedure such as drainage of plural fluid releases this compression and increase the oxygenation. However, the effect of pleural effusion on the elasticity of lung parenchyma is unknown.
arxiv
Cross Modal Global Local Representation Learning from Radiology Reports and X-Ray Chest Images [PDF]
arXiv, 2023 Deep learning models can be applied successfully in real-work problems; however, training most of these models requires massive data. Recent methods use language and vision, but unfortunately, they rely on datasets that are not usually publicly available.
arxiv
Cancer Communications, EarlyView.Abstract Background Bireociclib (XZP‐3287) is a novel selective cyclin‐dependent kinase 4 and 6 (CDK4/6) inhibitor, with a favorable safety profile demonstrated in preclinical and phase I studies. BRIGHT‐1 aimed to further explore the efficacy and safety of bireociclib monotherapy in patients with locally advanced, recurrent or metastatic, hormone ...
Jiayu Wang +18 more
wiley +1 more source
Can Deep Learning Reliably Recognize Abnormality Patterns on Chest X-rays? A Multi-Reader Study Examining One Month of AI Implementation in Everyday Radiology Clinical Practice [PDF]
arXiv, 2023 In this study, we developed a deep-learning-based automatic detection algorithm (DLAD, Carebot AI CXR) to detect and localize seven specific radiological findings (atelectasis (ATE), consolidation (CON), pleural effusion (EFF), pulmonary lesion (LES), subcutaneous emphysema (SCE), cardiomegaly (CMG), pneumothorax (PNO)) on chest X-rays (CXR).
arxiv
PLoS ONE, 2016 Objective The aim of our study was to evaluate the role of 18F-FDG PET/CT integrated imaging in differentiating malignant from benign pleural effusion.
Yajuan Sun +3 more
semanticscholar +1 more source
Reconstruction of Patient-Specific Confounders in AI-based Radiologic Image Interpretation using Generative Pretraining [PDF]
arXiv, 2023 Detecting misleading patterns in automated diagnostic assistance systems, such as those powered by Artificial Intelligence, is critical to ensuring their reliability, particularly in healthcare. Current techniques for evaluating deep learning models cannot visualize confounding factors at a diagnostic level.
arxiv