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We could show that using a deep learning approach to analyze MIR hyperspectral data obtained from benign and malignant lymph node pathology results in high accuracy for correct classification, learning the distinct region of 3900 to 850\u2009cm<jats:sup>\u22121<\/jats:sup>. The accuracy is above 95% for every pair of malignant lymphoid tissue and still above 90% for the distinction between benign and malignant lymphoid tissue for binary classification. These results demonstrate that a preliminary diagnosis and subtyping of human lymphoma could be streamlined by applying a deep learning approach to analyze MIR spectroscopic data.<\/jats:p><jats:p><jats:inline-graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"graphic\/jbio202300015-gra-0001.png\" xlink:title=\"image\"\/><\/jats:p>","DOI":"10.1002\/jbio.202300015","type":"journal-article","created":{"date-parts":[[2023,8,14]],"date-time":"2023-08-14T15:43:23Z","timestamp":1692027803000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Deep learning analysis of mid\u2010infrared microscopic imaging data for the diagnosis and classification of human lymphomas"],"prefix":"10.1002","volume":"16","author":[{"given":"P.","family":"Zelger","sequence":"first","affiliation":[{"name":"University Hospital of Hearing, Voice and Speech Disorders Medical University of Innsbruck  Innsbruck Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"A.","family":"Brunner","sequence":"additional","affiliation":[{"name":"Institute of Pathology, Neuropathology and Molecular Pathology Medical University of Innsbruck  Innsbruck Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"B.","family":"Zelger","sequence":"additional","affiliation":[{"name":"Institute of Pathology, Neuropathology and Molecular Pathology Medical University of Innsbruck  Innsbruck Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"E.","family":"Willenbacher","sequence":"additional","affiliation":[{"name":"University Hospital of Internal Medicine V, Hematology &amp; Oncology Medical University of Innsbruck  Innsbruck Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S. 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