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Oral cancers are often diagnosed at a late stage when treatment is less effective and the mortality and morbidity rates are high. Early detection of oral cancer is, therefore, crucial in order to improve the clinical outcomes. To investigate the potential of HSI as a noninvasive diagnostic tool, an animal study was designed to acquire hyperspectral images of in vivo and ex vivo mouse tongues from a chemically induced tongue carcinogenesis model. A variety of machine\u2010learning algorithms, including discriminant analysis, ensemble learning, and support vector machines, were evaluated for tongue neoplasia detection using HSI and were validated by the reconstructed pathological gold\u2010standard maps. The diagnostic performance of HSI, autofluorescence imaging, and fluorescence imaging were compared in this study. Color\u2010coded prediction maps were generated to display the predicted location and distribution of premalignant and malignant lesions. This study suggests that hyperspectral imaging combined with machine\u2010learning techniques can provide a noninvasive tool for the quantitative detection and delineation of squamous neoplasia.<\/jats:p><jats:p><jats:inline-graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"graphic\/jbio201700078-gra-0001.png\" xlink:title=\"image\"\/><\/jats:p>","DOI":"10.1002\/jbio.201700078","type":"journal-article","created":{"date-parts":[[2017,9,18]],"date-time":"2017-09-18T14:24:44Z","timestamp":1505744684000},"source":"Crossref","is-referenced-by-count":27,"title":["Detection and delineation of squamous neoplasia with hyperspectral imaging in a mouse model of tongue carcinogenesis"],"prefix":"10.1002","volume":"11","author":[{"given":"Guolan","family":"Lu","sequence":"first","affiliation":[{"name":"The Wallace H. 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