Jesper Ravn

Abstract The diagnosis of heart failure (HF) is resource-intensive, leading to severe underdiagnosis. This study proposes the use of a deep learning model to detect HF solely from electrocardiograms. HF has limited validity in diagnosis codes, lowering the viability of direct application of supervised learning. However, validating the codes with measured levels of circulating N-terminal proB-type natriuretic peptide (NT-proBNP) during training mitigates the impact of label noise.

ABSTRACT Pleural mesothelioma (PM) is a rare, aggressive malignancy of the pleura. The PM diagnosis is challenging, both in terms of imaging, sampling of representative biopsies and pathological examination, and the treatment options are limited. The main aim of this article is to summarize the most recent advances in the diagnosis and management of PM as presented in the Danish clinical guidelines for PM.

Back to Journals » Risk Management and Healthcare Policy » Volume 17 Authors Ranjbar A , Mork EW, Ravn J, Brøgger H, Myrseth P, Østrem HP, Hallock H Received 30 November 2023 Accepted for publication 20 March 2024 Published 10 April 2024 Volume 2024:17 Pages 877—882 DOI https://doi.org/10.2147/RMHP.S452337 Checked for plagiarism Yes Review by Single anonymous peer review Peer reviewer comments 2 Editor who approved publication: Dr Gulsum Kubra Kaya Arian Ranjbar,1 Eilin Wermundsen Mork,1...