{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T04:41:11Z","timestamp":1771476071581,"version":"3.50.1"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T00:00:00Z","timestamp":1747180800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T00:00:00Z","timestamp":1747180800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/100000002","name":"U.S. Department of Health & Human Services | National Institutes of Health","doi-asserted-by":"publisher","award":["R61NS113341"],"award-info":[{"award-number":["R61NS113341"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["npj Digit. Med."],"DOI":"10.1038\/s41746-025-01577-3","type":"journal-article","created":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T07:26:36Z","timestamp":1747207596000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Development and validation of a deep learning model for diagnosing neuropathic corneal pain via in vivo confocal microscopy"],"prefix":"10.1038","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9268-1461","authenticated-orcid":false,"given":"Neslihan Dilruba","family":"Koseoglu","sequence":"first","affiliation":[]},{"given":"Eric","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Rudraksh","family":"Tuwani","sequence":"additional","affiliation":[]},{"given":"Benjamin","family":"Kompa","sequence":"additional","affiliation":[]},{"given":"Stephanie M.","family":"Cox","sequence":"additional","affiliation":[]},{"given":"M.","family":"Cuneyt Ozmen","sequence":"additional","affiliation":[]},{"given":"Mina","family":"Massaro-Giordano","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6657-2787","authenticated-orcid":false,"given":"Andrew L.","family":"Beam","sequence":"additional","affiliation":[]},{"given":"Pedram","family":"Hamrah","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,5,14]]},"reference":[{"key":"1577_CR1","doi-asserted-by":"publisher","first-page":"59","DOI":"10.3109\/08820538.2015.1114853","volume":"31","author":"S Goyal","year":"2016","unstructured":"Goyal, S. & Hamrah, P. Understanding neuropathic corneal pain\u2013gaps and current therapeutic approaches. Semin Ophthalmol. 31, 59\u201370 (2016).","journal-title":"Semin Ophthalmol."},{"key":"1577_CR2","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1016\/j.jtos.2017.10.001","volume":"16","author":"A Galor","year":"2018","unstructured":"Galor, A. et al. Neuropathic pain and dry eye. Ocul. Surf. 16, 31\u201344 (2018).","journal-title":"Ocul. Surf."},{"key":"1577_CR3","doi-asserted-by":"publisher","first-page":"S34","DOI":"10.1016\/j.ophtha.2017.08.004","volume":"124","author":"G Dieckmann","year":"2017","unstructured":"Dieckmann, G., Goyal, S. & Hamrah, P. Neuropathic corneal pain: approaches for management. Ophthalmology 124, S34\u2013s47 (2017).","journal-title":"Ophthalmology"},{"key":"1577_CR4","doi-asserted-by":"publisher","first-page":"2427","DOI":"10.1016\/j.pain.2011.06.006","volume":"152","author":"D Borsook","year":"2011","unstructured":"Borsook, D. & Rosenthal, P. Chronic (neuropathic) corneal pain and blepharospasm: five case reports. Pain 152, 2427\u20132431 (2011).","journal-title":"Pain"},{"key":"1577_CR5","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1097\/ICO.0b013e3181f7f363","volume":"30","author":"J Yu","year":"2011","unstructured":"Yu, J., Asche, C. V. & Fairchild, C. J. The economic burden of dry eye disease in the United States: a decision tree analysis. Cornea 30, 379\u2013387 (2011).","journal-title":"Cornea"},{"key":"1577_CR6","first-page":"2656","volume":"58","author":"H-R Moein","year":"2017","unstructured":"Moein, H. -R. et al. In vivo confocal microscopy demonstrates the presence of microneuromas and may allow differentiation of patients with corneal neuropathic pain from dry eye disease. Investig. Ophthalmol. Vis. Sci. 58, 2656\u20132656 (2017).","journal-title":"Investig. Ophthalmol. Vis. Sci."},{"key":"1577_CR7","doi-asserted-by":"publisher","first-page":"651","DOI":"10.1016\/j.jtos.2020.07.004","volume":"18","author":"HR Moein","year":"2020","unstructured":"Moein, H. R. et al. Visualization of microneuromas by using in vivo confocal microscopy: An objective biomarker for the diagnosis of neuropathic corneal pain?. Ocul. Surf. 18, 651\u2013656 (2020).","journal-title":"Ocul. Surf."},{"key":"1577_CR8","doi-asserted-by":"publisher","first-page":"250","DOI":"10.1016\/j.jtos.2015.01.005","volume":"13","author":"S Aggarwal","year":"2015","unstructured":"Aggarwal, S. et al. Autologous serum tears for treatment of photoallodynia in patients with corneal neuropathy: efficacy and evaluation with in vivo confocal microscopy. Ocul. Surf. 13, 250\u2013262 (2015).","journal-title":"Ocul. Surf."},{"key":"1577_CR9","doi-asserted-by":"publisher","first-page":"532","DOI":"10.1016\/j.jtos.2019.01.009","volume":"17","author":"S Aggarwal","year":"2019","unstructured":"Aggarwal, S., Colon, C., Kheirkhah, A. & Hamrah, P. Efficacy of autologous serum tears for treatment of neuropathic corneal pain. Ocul. Surf. 17, 532\u2013539 (2019).","journal-title":"Ocul. Surf."},{"key":"1577_CR10","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1016\/j.jtos.2017.10.003","volume":"16","author":"MI Morkin","year":"2018","unstructured":"Morkin, M. I. & Hamrah, P. Efficacy of self-retained cryopreserved amniotic membrane for treatment of neuropathic corneal pain. Ocul. Surf. 16, 132\u2013138 (2018).","journal-title":"Ocul. Surf."},{"key":"1577_CR11","doi-asserted-by":"publisher","unstructured":"Olcucu, O., de Leeuw, A., Lamazales, L. L., Mallone, F. & Hamrah, P. Efficacy of extranasal neurostimulation for patients with neuropathic corneal pain: a pilot study. Cornea, 10.1097\/ICO.0000000000003719 https:\/\/doi.org\/10.1097\/ico.0000000000003719 (9900).","DOI":"10.1097\/ico.0000000000003719"},{"key":"1577_CR12","doi-asserted-by":"publisher","first-page":"1107","DOI":"10.1111\/ner.13402","volume":"24","author":"D Mehra","year":"2021","unstructured":"Mehra, D. et al. Long-term trigeminal nerve stimulation as a treatment for ocular pain. Neuromodulation 24, 1107\u20131114 (2021).","journal-title":"Neuromodulation"},{"key":"1577_CR13","doi-asserted-by":"publisher","first-page":"814","DOI":"10.1016\/j.jtos.2020.08.006","volume":"18","author":"MC Ozmen","year":"2020","unstructured":"Ozmen, M. C. et al. Efficacy and tolerability of nortriptyline in the management of neuropathic corneal pain. Ocul. Surf. 18, 814\u2013820 (2020).","journal-title":"Ocul. Surf."},{"key":"1577_CR14","doi-asserted-by":"publisher","unstructured":"Yoon, H. J., Kim, J. & Yoon, K. C. Treatment response to gabapentin in neuropathic ocular pain associated with dry eye. J. Clin. Med. 9 https:\/\/doi.org\/10.3390\/jcm9113765 (2020).","DOI":"10.3390\/jcm9113765"},{"key":"1577_CR15","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1016\/j.jtos.2020.12.003","volume":"20","author":"G Dieckmann","year":"2021","unstructured":"Dieckmann, G., Ozmen, M. C., Cox, S. M., Engert, R. C. & Hamrah, P. Low-dose naltrexone is effective and well-tolerated for modulating symptoms in patients with neuropathic corneal pain. Ocul. Surf. 20, 33\u201338 (2021).","journal-title":"Ocul. Surf."},{"key":"1577_CR16","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1016\/S1542-0124(12)70290-2","volume":"7","author":"P Rosenthal","year":"2009","unstructured":"Rosenthal, P., Baran, I. & Jacobs, D. S. Corneal pain without stain: is it real?. Ocul. Surf. 7, 28\u201340 (2009).","journal-title":"Ocul. Surf."},{"key":"1577_CR17","doi-asserted-by":"publisher","unstructured":"Guerrero-Moreno, A. et al. Corneal nerve abnormalities in painful dry eye disease patients. Biomedicines 9 https:\/\/doi.org\/10.3390\/biomedicines9101424 (2021).","DOI":"10.3390\/biomedicines9101424"},{"key":"1577_CR18","unstructured":"Moshirfar, M. & Benstead, E. E., Sorrentino, P. M. & Tripathy, K. in StatPearls (StatPearls Publishing Copyright \u00a9 2023, StatPearls Publishing LLC., 2023)."},{"key":"1577_CR19","doi-asserted-by":"publisher","first-page":"e233","DOI":"10.1097\/OPX.0000000000000652","volume":"92","author":"C Theophanous","year":"2015","unstructured":"Theophanous, C., Jacobs, D. S. & Hamrah, P. Corneal neuralgia after LASIK. Optom. Vis. Sci. 92, e233\u2013e240 (2015).","journal-title":"Optom. Vis. Sci."},{"key":"1577_CR20","doi-asserted-by":"publisher","first-page":"768","DOI":"10.1136\/bjophthalmol-2019-314799","volume":"104","author":"AR Ross","year":"2020","unstructured":"Ross, A. R. et al. Clinical and in vivo confocal microscopic features of neuropathic corneal pain. Br. J. Ophthalmol. 104, 768\u2013775 (2020).","journal-title":"Br. J. Ophthalmol."},{"key":"1577_CR21","doi-asserted-by":"publisher","first-page":"641","DOI":"10.1016\/j.jtos.2020.07.006","volume":"18","author":"BN Bayraktutar","year":"2020","unstructured":"Bayraktutar, B. N. et al. Comparison of clinical characteristics of post-refractive surgery-related and post-herpetic neuropathic corneal pain. Ocul. Surf. 18, 641\u2013650 (2020).","journal-title":"Ocul. Surf."},{"key":"1577_CR22","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.jtos.2016.09.004","volume":"15","author":"A Cruzat","year":"2017","unstructured":"Cruzat, A., Qazi, Y. & Hamrah, P. In vivo confocal microscopy of corneal nerves in health and disease. Ocul. Surf. 15, 15\u201347 (2017).","journal-title":"Ocul. Surf."},{"key":"1577_CR23","doi-asserted-by":"publisher","first-page":"1656","DOI":"10.4103\/IJO.IJO_2835_22","volume":"71","author":"S D\u2019Souza","year":"2023","unstructured":"D\u2019Souza, S., Khamar, P. & Shetty, R. Fibromyalgia syndrome and the eye-Implications in corneal ultrastructure on confocal microscopy. Indian J. Ophthalmol. 71, 1656\u20131657 (2023).","journal-title":"Indian J. Ophthalmol."},{"key":"1577_CR24","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1136\/bjophthalmol-2014-306280","volume":"100","author":"P Rosenthal","year":"2016","unstructured":"Rosenthal, P. & Borsook, D. Ocular neuropathic pain. Br. J. Ophthalmol. 100, 128\u2013134 (2016).","journal-title":"Br. J. Ophthalmol."},{"key":"1577_CR25","unstructured":"The Study Assessing the Safety and Efficacy of OK-101 Treatment in Subjects With Neuropathic Corneal Pain, https:\/\/clinicaltrials.gov\/study\/NCT06637527?cond=neuropathic%20corneal%20pain%20&term=OK-101&rank=1."},{"key":"1577_CR26","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1007\/s11910-019-1020-1","volume":"19","author":"K Farhad","year":"2019","unstructured":"Farhad, K. Current diagnosis and treatment of painful small fiber neuropathy. Curr. Neurol. Neurosci. Rep. 19, 103 (2019).","journal-title":"Curr. Neurol. Neurosci. Rep."},{"key":"1577_CR27","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1167\/tvst.9.2.32","volume":"9","author":"S Wei","year":"2020","unstructured":"Wei, S., Shi, F., Wang, Y., Chou, Y. & Li, X. A deep learning model for automated sub-basal corneal nerve segmentation and evaluation using in vivo confocal microscopy. Transl. Vis. Sci. Technol. 9, 32 (2020).","journal-title":"Transl. Vis. Sci. Technol."},{"key":"1577_CR28","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1002\/cyto.a.20022","volume":"58","author":"E Meijering","year":"2004","unstructured":"Meijering, E. et al. Design and validation of a tool for neurite tracing and analysis in fluorescence microscopy images. Cytom. A 58, 167\u2013176 (2004).","journal-title":"Cytom. A"},{"key":"1577_CR29","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y. & Hinton, G. Deep learning. Nature 521, 436\u2013444 (2015).","journal-title":"Nature"},{"key":"1577_CR30","doi-asserted-by":"publisher","first-page":"1101","DOI":"10.1001\/jama.2018.11100","volume":"320","author":"G Hinton","year":"2018","unstructured":"Hinton, G. Deep learning-a technology with the potential to transform health care. Jama 320, 1101\u20131102 (2018).","journal-title":"Jama"},{"key":"1577_CR31","doi-asserted-by":"crossref","unstructured":"Ben-David, S. & Shalev-Shwartz, S. Understanding Machine Learning: From Theory to Algorithms (Cambridge University Press, 2014).","DOI":"10.1017\/CBO9781107298019"},{"key":"1577_CR32","doi-asserted-by":"publisher","first-page":"1317","DOI":"10.1001\/jama.2017.18391","volume":"319","author":"AL Beam","year":"2018","unstructured":"Beam, A. L. & Kohane, I. S. Big data and machine learning in health care. Jama 319, 1317\u20131318 (2018).","journal-title":"Jama"},{"key":"1577_CR33","doi-asserted-by":"publisher","first-page":"1606","DOI":"10.1016\/j.spinee.2020.08.012","volume":"21","author":"A Schmaltz","year":"2021","unstructured":"Schmaltz, A. & Beam, A. L. Sharpening the resolution on data matters: a brief roadmap for understanding deep learning for medical data. Spine J. 21, 1606\u20131609 (2021).","journal-title":"Spine J."},{"key":"1577_CR34","doi-asserted-by":"publisher","first-page":"e1914051","DOI":"10.1001\/jamanetworkopen.2019.14051","volume":"2","author":"B Beaulieu-Jones","year":"2019","unstructured":"Beaulieu-Jones, B. et al. Trends and focus of machine learning applications for health research. JAMA Netw. Open 2, e1914051 (2019).","journal-title":"JAMA Netw. Open"},{"key":"1577_CR35","doi-asserted-by":"publisher","first-page":"719","DOI":"10.1038\/s41551-018-0305-z","volume":"2","author":"KH Yu","year":"2018","unstructured":"Yu, K. H., Beam, A. L. & Kohane, I. S. Artificial intelligence in healthcare. Nat. Biomed. Eng. 2, 719\u2013731 (2018).","journal-title":"Nat. Biomed. Eng."},{"key":"1577_CR36","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1038\/s41746-020-00367-3","volume":"4","author":"B Kompa","year":"2021","unstructured":"Kompa, B., Snoek, J. & Beam, A. L. Second opinion needed: communicating uncertainty in medical machine learning. NPJ Digit. Med. 4, 4 (2021).","journal-title":"NPJ Digit. Med."},{"key":"1577_CR37","doi-asserted-by":"publisher","unstructured":"Kompa, B., Snoek, J. & Beam, A. L. Empirical frequentist coverage of deep learning uncertainty quantification procedures. Entropy 23 https:\/\/doi.org\/10.3390\/e23121608 (2021).","DOI":"10.3390\/e23121608"},{"key":"1577_CR38","unstructured":"Sundararajan, M., Taly, A. & Yan, Q. Axiomatic attribution for deep networks. In Proc. of the 34th International Conference on Machine Learning, Sydney, Australia, PMLR, Vol. 70, 3319\u20133328 (2017)."},{"key":"1577_CR39","doi-asserted-by":"publisher","first-page":"e745","DOI":"10.1016\/S2589-7500(21)00208-9","volume":"3","author":"M Ghassemi","year":"2021","unstructured":"Ghassemi, M., Oakden-Rayner, L. & Beam, A. L. The false hope of current approaches to explainable artificial intelligence in health care. Lancet Digit. Health 3, e745\u2013e750 (2021).","journal-title":"Lancet Digit. Health"},{"key":"1577_CR40","doi-asserted-by":"publisher","first-page":"574","DOI":"10.1111\/jdi.13381","volume":"12","author":"M Wang","year":"2021","unstructured":"Wang, M. et al. Diagnostic utility of corneal confocal microscopy in type 2 diabetic peripheral neuropathy. J. Diab. Investig. 12, 574\u2013582 (2021).","journal-title":"J. Diab. Investig."},{"key":"1577_CR41","doi-asserted-by":"publisher","first-page":"1340","DOI":"10.1016\/S0140-6736(05)67546-0","volume":"366","author":"P Hossain","year":"2005","unstructured":"Hossain, P., Sachdev, A. & Malik, R. A. Early detection of diabetic peripheral neuropathy with corneal confocal microscopy. Lancet 366, 1340\u20131343 (2005).","journal-title":"Lancet"},{"key":"1577_CR42","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1186\/s40662-020-00192-5","volume":"7","author":"JD Oakley","year":"2020","unstructured":"Oakley, J. D. et al. Deep learning-based analysis of macaque corneal sub-basal nerve fibers in confocal microscopy images. Eye Vis.7, 27 (2020).","journal-title":"Eye Vis."},{"key":"1577_CR43","doi-asserted-by":"publisher","first-page":"1847","DOI":"10.1177\/1352458516677590","volume":"23","author":"J Mikolajczak","year":"2017","unstructured":"Mikolajczak, J. et al. Patients with multiple sclerosis demonstrate reduced subbasal corneal nerve fibre density. Mult. Scler. 23, 1847\u20131853 (2017).","journal-title":"Mult. Scler."},{"key":"1577_CR44","unstructured":"Prospective Study to Validate the Imaging Biomarker for NCP (R33)."},{"key":"1577_CR45","first-page":"4199","volume":"60","author":"ND Koseoglu","year":"2019","unstructured":"Koseoglu, N. D. et al. Patients with clinical signs of dry eye disease demonstrate presence of signs of neuropathic corneal pain. Investig. Ophthalmol. Vis. Sci. 60, 4199\u20134199 (2019).","journal-title":"Investig. Ophthalmol. Vis. Sci."},{"key":"1577_CR46","doi-asserted-by":"publisher","first-page":"e048008","DOI":"10.1136\/bmjopen-2020-048008","volume":"11","author":"GS Collins","year":"2021","unstructured":"Collins, G. S. et al. Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence. BMJ Open 11, e048008 (2021).","journal-title":"BMJ Open"},{"key":"1577_CR47","doi-asserted-by":"crossref","unstructured":"Girshick, R. B., Donahue, J., Darrell, T. & Malik, J. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation. 2014 IEEE Conference on Computer Vision and Pattern Recognition, 580\u2013587 (2013).","DOI":"10.1109\/CVPR.2014.81"},{"key":"1577_CR48","unstructured":"Tan, M. & Le, Q. V. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. ArXiv abs\/1905.11946 (2019)."},{"key":"1577_CR49","unstructured":"Zhang, H., Ciss\u00e9, M., Dauphin, Y. & Lopez-Paz, D. mixup: Beyond Empirical Risk Minimization. ArXiv abs\/1710.09412 (2017)."},{"key":"1577_CR50","doi-asserted-by":"publisher","first-page":"2839","DOI":"10.1016\/j.patcog.2015.03.009","volume":"48","author":"T-T Wong","year":"2015","unstructured":"Wong, T. -T. Performance evaluation of classification algorithms by k-fold and leave-one-out cross validation. Pattern Recognit. 48, 2839\u20132846 (2015).","journal-title":"Pattern Recognit."}],"container-title":["npj Digital Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-01577-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-01577-3","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-01577-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T07:26:43Z","timestamp":1747207603000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-01577-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,14]]},"references-count":50,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["1577"],"URL":"https:\/\/doi.org\/10.1038\/s41746-025-01577-3","relation":{},"ISSN":["2398-6352"],"issn-type":[{"value":"2398-6352","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,14]]},"assertion":[{"value":"19 April 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 March 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 May 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests. Patent applicant: Harvard College, Tufts Medical Center. Name of inventors: Pedram HAMRAH, Neslihan Dilruba KOSEOGLU, Andrew BEAM. Patent number: US20210113078A1.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"277"}}