{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T14:16:25Z","timestamp":1790172985929,"version":"4.1.0"},"reference-count":43,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2025,11,22]],"date-time":"2025-11-22T00:00:00Z","timestamp":1763769600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,11,22]],"date-time":"2025-11-22T00:00:00Z","timestamp":1763769600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100008982","name":"Qatar National Research Fund","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100008982","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Ann Clin Transl Neurol"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning\u2013based multiclass classification system for rapid, automated diagnosis and differentiation of 88 patients with diabetic peripheral neuropathy (DPN), chemotherapy\u2010induced peripheral neuropathy (CIPN), chronic inflammatory demyelinating polyneuropathy (CIDP), and human immunodeficiency virus\u2010associated sensory neuropathy (HIV\u2010SN).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A deep learning\u2013based multiclass system was developed to analyze corneal nerve images. These images were preprocessed to train and validate the proposed model and the diagnostic utility was evaluated from the accuracy,\n                      <jats:italic>F1<\/jats:italic>\n                      \u2010score and area under the curve to derive sensitivity, specificity and precision.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>NeuropathAI achieved excellent results: AUC\u201496.75%, sensitivity\u201483.87%, specificity\u201495.07%, and demonstrated excellent discrimination for CIDP, CIPN, HIV\u2010SN and DPN with one\u2010vs\u2010all AUC scores of 97%, 93.1%, 99.7% and 96.9%, respectively. Explainability visualization through heatmaps demonstrated that regions of decision making by the model localized to areas with nerve fiber loss, enhancing interpretability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Interpretation<\/jats:title>\n                    <jats:p>NeuropathAI achieved rapid and accurate diagnosis of four of the most prevalent peripheral neuropathies globally, underscoring the potential of artificial intelligence\u2013driven corneal image analysis for the rapid diagnosis and differentiation of peripheral neuropathies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/acn3.70255","type":"journal-article","created":{"date-parts":[[2025,11,23]],"date-time":"2025-11-23T02:33:44Z","timestamp":1763865224000},"page":"747-754","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Deep Learning\u2013Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy"],"prefix":"10.1002","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4153-3287","authenticated-orcid":false,"given":"Chaima Ben","family":"Rabah","sequence":"first","affiliation":[{"name":"AI Innovation Lab Weill Cornell Medicine  Doha Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ioannis N.","family":"Petropoulos","sequence":"additional","affiliation":[{"name":"Division of Research Weill Cornell Medicine  Doha Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8836-0443","authenticated-orcid":false,"given":"Mark","family":"Stettner","sequence":"additional","affiliation":[{"name":"Department of Neurology and Center for Translational Neuro\u2010 and Behavioral Sciences (C\u2010TNBS) University Hospital Essen  Essen Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maryam","family":"Ferdousi","sequence":"additional","affiliation":[{"name":"Faculty of Biology, Medicine and Health University of Manchester  Manchester UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Uazman","family":"Alam","sequence":"additional","affiliation":[{"name":"Diabetes &amp; Obesity Research, Department of Medicine Aintree University Hospital  Liverpool UK"},{"name":"Stoke\u2010on\u2010Trent, Centre for Biomechanics and Rehabilitation Technologies Staffordshire University  UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nathan","family":"Efron","sequence":"additional","affiliation":[{"name":"Institute of Health and Biomedical Innovation Queensland University of Technology  Brisbane Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmed","family":"Serag","sequence":"additional","affiliation":[{"name":"AI Innovation Lab Weill Cornell Medicine  Doha Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7188-8903","authenticated-orcid":false,"given":"Rayaz A.","family":"Malik","sequence":"additional","affiliation":[{"name":"Division of Research Weill Cornell Medicine  Doha Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,11,22]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1474-4422(24)00038-3"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamaneurol.2022.0565"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.mayocp.2015.05.004"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.39192.488125.BE"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1111\/jns.12613"},{"key":"e_1_2_10_7_1","first-page":"435","article-title":"Clinical Applications of Corneal Confocal Microscopy","volume":"2","author":"Tavakoli M.","year":"2008","journal-title":"Clinical Ophthalmology"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(05)67546-0"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1167\/iovs.13-13787"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.3390\/jcm11175130"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1167\/iovs.14-15919"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1136\/bjophthalmol-2014-306038"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.clinthera.2021.04.003"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.2337\/dc14-2114"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1111\/jdi.13643"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.expneurol.2009.08.033"},{"key":"e_1_2_10_17_1","first-page":"1361","article-title":"Neurophysiological, Nerve Imaging and Other Techniques to Assess Chemotherapy\u2010Induced Peripheral Neurotoxicity in the Clinical and Research Settings","volume":"90","author":"Argyriou A. 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