{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T15:34:01Z","timestamp":1781019241292,"version":"3.54.1"},"reference-count":40,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2020,11,24]],"date-time":"2020-11-24T00:00:00Z","timestamp":1606176000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"College of Engineering Scientific Research Center"},{"name":"Deanship of Scientific Research of King Khalid University","award":["R.G.P.I\/202\/41"],"award-info":[{"award-number":["R.G.P.I\/202\/41"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,1,19]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Discovering oral cavity cancer (OCC) at an early stage is an effective way to increase patient survival rate. However, current initial screening process is done manually and is expensive for the average individual, especially in developing countries worldwide. This problem is further compounded due to the lack of specialists in such areas. Automating the initial screening process using artificial intelligence (AI) to detect pre-cancerous lesions can prove to be an effective and inexpensive technique that would allow patients to be triaged accordingly to receive appropriate clinical management. In this study, we have applied and evaluated the efficacy of six deep convolutional neural network (DCNN) models using transfer learning, for identifying pre-cancerous tongue lesions directly using a small dataset of clinically annotated photographic images to diagnose early signs of OCC. DCNN models were able to differentiate between benign and pre-cancerous tongue lesions and were also able to distinguish between five types of tongue lesions, i.e. hairy tongue, fissured tongue, geographic tongue, strawberry tongue and oral hairy leukoplakia with high classification performances. Preliminary results using an (AI + Physician) ensemble model demonstrate that an automated pre-screening process of oral tongue lesions using DCNNs can achieve \u2018near-human\u2019 level classification performance for diagnosing early signs of OCC in patients.<\/jats:p>","DOI":"10.1093\/comjnl\/bxaa136","type":"journal-article","created":{"date-parts":[[2020,10,1]],"date-time":"2020-10-01T03:19:40Z","timestamp":1601522380000},"page":"91-104","source":"Crossref","is-referenced-by-count":101,"title":["Automated Detection of Oral Pre-Cancerous Tongue Lesions Using Deep Learning for Early Diagnosis of Oral Cavity Cancer"],"prefix":"10.1093","volume":"65","author":[{"given":"Mohammed Zubair M","family":"Shamim","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, College of Engineering, King Khalid University, Abha 62529, Saudi Arabia"},{"name":"Center for Artificial Intelligence, King Khalid University, Abha 61413, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sadatullah","family":"Syed","sequence":"additional","affiliation":[{"name":"Department of Diagnostic Sciences and Oral Biology, College of Dentistry, King Khalid University, Abha 61471, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad","family":"Shiblee","sequence":"additional","affiliation":[{"name":"Deanship of University Development, Taif University, Taif 21974, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammed","family":"Usman","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, College of Engineering, King Khalid University, Abha 62529, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4834-3593","authenticated-orcid":false,"given":"Syed Jaffar","family":"Ali","sequence":"additional","affiliation":[{"name":"Computer Engineering Department, King Khalid University, Abha 61413, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4929-0702","authenticated-orcid":false,"given":"Hany S","family":"Hussein","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, College of Engineering, King Khalid University, Abha 62529, Saudi Arabia"},{"name":"Electrical Engineering Department, Faculty of Engineering, Aswan University, Aswan 81542, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammed","family":"Farrag","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, College of Engineering, King Khalid University, Abha 62529, Saudi Arabia"},{"name":"Electrical Engineering Department, Assiut University, Assiut 71515, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2020,11,24]]},"reference":[{"key":"2022011721241581100_ref1","doi-asserted-by":"crossref","first-page":"394","DOI":"10.3322\/caac.21492","article-title":"Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"68","author":"Bray","year":"2018","journal-title":"Cancer J. 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