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Papers of the Week

Papers: 25 Mar 2023 - 31 Mar 2023

Methodology, Translational

Human Studies, In Silico Studies, Medical Devices

2023 Mar 28

Orphanet J Rare Dis




A diagnostic support system based on pain drawings: binary and k-disease classification of EDS, GBS, FSHD, PROMM, and a control group with Pain2D.


Emmert D, Szczypien N, Bender TTA, Grigull L, Gass A, Link C, Klawonn F, Conrad R, Mücke M, Sellin J


The diagnosis of rare diseases (RDs) is often challenging due to their rarity, variability and the high number of individual RDs, resulting in a delay in diagnosis with adverse effects for patients and healthcare systems. The development of computer assisted diagnostic decision support systems could help to improve these problems by supporting differential diagnosis and by prompting physicians to initiate the right diagnostic tests. Towards this end, we developed, trained and tested a machine learning model implemented as part of the software called Pain2D to classify four rare diseases (EDS, GBS, FSHD and PROMM), as well as a control group of unspecific chronic pain, from pen-and-paper pain drawings filled in by patients.