Towards reliable use of artificial intelligence to classify otitis media using otoscopic images: Addressing bias and improving data quality.
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| Title: | Towards reliable use of artificial intelligence to classify otitis media using otoscopic images: Addressing bias and improving data quality. |
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| Authors: | Xu Y; AI for Good Lab, Microsoft, Redmond, Washington, United States of America., Habib AR; Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Camperdown, New South Wales, Australia.; Department of Otolaryngology, Head and Neck Surgery, Westmead Hospital, Sydney, New South Wales, Australia.; Department of Otolaryngology - Head and Neck Surgery, Queensland Children's Hospital, South Brisbane, Queensland, Australia., Crossland G; Department of Otolaryngology - Head and Neck Surgery, Royal Darwin Hospital, Tiwi, Northern Territory, Australia., Patel H; Department of Otolaryngology - Head and Neck Surgery, Royal Darwin Hospital, Tiwi, Northern Territory, Australia., Perry C; University of Queensland Medical School, Brisbane, Queensland, Australia., Bock K; Azure FastTrack Engineering, Microsoft, Brisbane, Queensland, Australia., Lian T; Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Camperdown, New South Wales, Australia.; Department of Otolaryngology, Head and Neck Surgery, Westmead Hospital, Sydney, New South Wales, Australia., Weeks WB; AI for Good Lab, Microsoft, Redmond, Washington, United States of America., Dodhia R; AI for Good Lab, Microsoft, Redmond, Washington, United States of America., Ferres JL; AI for Good Lab, Microsoft, Redmond, Washington, United States of America., Singh NP; Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Camperdown, New South Wales, Australia.; Department of Otolaryngology, Head and Neck Surgery, Westmead Hospital, Sydney, New South Wales, Australia. |
| Source: | PloS one [PLoS One] 2026 May 07; Vol. 21 (5), pp. e0338867. Date of Electronic Publication: 2026 May 07 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0338867 |
