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    • Mashup Score: 27
      Detection of large flat colorectal lesions by artificial intelligence: a persistent weakness and blind spot - 5 month(s) ago

      Computer-aided detection (CADe) has increased adenoma detection in randomised trials. However, unlike other detection adjuncts, CADe is lesion specific, that is, it is trained on a specific set of lesions. If the training does not include sufficient examples of precancerous lesion subsets, CADe may not perform adequately for lesions in that subset. In a prospective assessment of a second-generation CADe programme in 165 colonoscopies, we identified 26 flat lesions ≥10 mm in 17 patients. The endoscopist identified 22 of 26 lesions before the CADe programme. In 13 lesions, the CADe either generated no detection signal or only a signal over part of the lesion after colonoscope position or luminal inflation adjustment. Thus, the second-generation CADe algorithm, like the first generation, frequently fails to effectively detect large flat colorectal lesions, which are likely very important lesions that a CADe programme should identify. The first CADe programme to be launched commercially in

      Source: gut.bmj.com
      Categories: General Medicine News, Gastroenterology
      Tweet Tweets with this article
      • Profile photo of 	Gut_BMJ
        Gut_BMJ

        #EndoscopyNews paper by @Rex_colonoscopy et al on "Detection of large flat colorectal lesions by artificial intelligence: a persistent weakness and blind spot" via https://t.co/sCwdmL8OXO @JohnGuardiolaMD #AI https://t.co/4g23yzIDN9

    • Mashup Score: 26
      Detection of large flat colorectal lesions by artificial intelligence: a persistent weakness and blind spot - 5 month(s) ago

      Computer-aided detection (CADe) has increased adenoma detection in randomised trials. However, unlike other detection adjuncts, CADe is lesion specific, that is, it is trained on a specific set of lesions. If the training does not include sufficient examples of precancerous lesion subsets, CADe may not perform adequately for lesions in that subset. In a prospective assessment of a second-generation CADe programme in 165 colonoscopies, we identified 26 flat lesions ≥10 mm in 17 patients. The endoscopist identified 22 of 26 lesions before the CADe programme. In 13 lesions, the CADe either generated no detection signal or only a signal over part of the lesion after colonoscope position or luminal inflation adjustment. Thus, the second-generation CADe algorithm, like the first generation, frequently fails to effectively detect large flat colorectal lesions, which are likely very important lesions that a CADe programme should identify. The first CADe programme to be launched commercially in

      Source: gut.bmj.com
      Categories: General Medicine News, Gastroenterology
      Tweet Tweets with this article
      • Profile photo of 	Gut_BMJ
        Gut_BMJ

        #EndoscopyNews paper by @Rex_colonoscopy et al on "Detection of large flat colorectal lesions by artificial intelligence: a persistent weakness and blind spot" via https://t.co/sCwdmL8OXO @JohnGuardiolaMD #AI https://t.co/4g23yzIDN9

    • Mashup Score: 27
      Detection of large flat colorectal lesions by artificial intelligence: a persistent weakness and blind spot - 5 month(s) ago

      Computer-aided detection (CADe) has increased adenoma detection in randomised trials. However, unlike other detection adjuncts, CADe is lesion specific, that is, it is trained on a specific set of lesions. If the training does not include sufficient examples of precancerous lesion subsets, CADe may not perform adequately for lesions in that subset. In a prospective assessment of a second-generation CADe programme in 165 colonoscopies, we identified 26 flat lesions ≥10 mm in 17 patients. The endoscopist identified 22 of 26 lesions before the CADe programme. In 13 lesions, the CADe either generated no detection signal or only a signal over part of the lesion after colonoscope position or luminal inflation adjustment. Thus, the second-generation CADe algorithm, like the first generation, frequently fails to effectively detect large flat colorectal lesions, which are likely very important lesions that a CADe programme should identify. The first CADe programme to be launched commercially in

      Source: gut.bmj.com
      Categories: General Medicine News, Gastroenterology
      Tweet Tweets with this article
      • Profile photo of 	Gut_BMJ
        Gut_BMJ

        #EndoscopyNews paper by @Rex_colonoscopy et al on "Detection of large flat colorectal lesions by artificial intelligence: a persistent weakness and blind spot" via https://t.co/sCwdmL8OXO @JohnGuardiolaMD #AI https://t.co/4g23yzIDN9

    • Mashup Score: 25
      Detection of large flat colorectal lesions by artificial intelligence: a persistent weakness and blind spot - 6 month(s) ago

      Computer-aided detection (CADe) has increased adenoma detection in randomised trials. However, unlike other detection adjuncts, CADe is lesion specific, that is, it is trained on a specific set of lesions. If the training does not include sufficient examples of precancerous lesion subsets, CADe may not perform adequately for lesions in that subset. In a prospective assessment of a second-generation CADe programme in 165 colonoscopies, we identified 26 flat lesions ≥10 mm in 17 patients. The endoscopist identified 22 of 26 lesions before the CADe programme. In 13 lesions, the CADe either generated no detection signal or only a signal over part of the lesion after colonoscope position or luminal inflation adjustment. Thus, the second-generation CADe algorithm, like the first generation, frequently fails to effectively detect large flat colorectal lesions, which are likely very important lesions that a CADe programme should identify. The first CADe programme to be launched commercially in

      Source: gut.bmj.com
      Categories: General Medicine News, Gastroenterology
      Tweet Tweets with this article
      • Profile photo of 	Gut_BMJ
        Gut_BMJ

        #EndoscopyNews paper by @Rex_colonoscopy et al on "Detection of large flat colorectal lesions by artificial intelligence: a persistent weakness and blind spot" via https://t.co/sCwdmL8OXO @JohnGuardiolaMD #AI https://t.co/4g23yzIDN9

    • Mashup Score: 16
      Detection of large flat colorectal lesions by artificial intelligence: a persistent weakness and blind spot - 6 month(s) ago

      Computer-aided detection (CADe) has increased adenoma detection in randomised trials. However, unlike other detection adjuncts, CADe is lesion specific, that is, it is trained on a specific set of lesions. If the training does not include sufficient examples of precancerous lesion subsets, CADe may not perform adequately for lesions in that subset. In a prospective assessment of a second-generation CADe programme in 165 colonoscopies, we identified 26 flat lesions ≥10 mm in 17 patients. The endoscopist identified 22 of 26 lesions before the CADe programme. In 13 lesions, the CADe either generated no detection signal or only a signal over part of the lesion after colonoscope position or luminal inflation adjustment. Thus, the second-generation CADe algorithm, like the first generation, frequently fails to effectively detect large flat colorectal lesions, which are likely very important lesions that a CADe programme should identify. The first CADe programme to be launched commercially in

      Source: gut.bmj.com
      Categories: General Medicine News, Gastroenterology
      Tweet Tweets with this article
      • Profile photo of 	Gut_BMJ
        Gut_BMJ

        #EndoscopyNews paper by @Rex_colonoscopy et al on "Detection of large flat colorectal lesions by artificial intelligence: a persistent weakness and blind spot" via https://t.co/sCwdmL8OXO @JohnGuardiolaMD #AI https://t.co/xlWD38wOOw

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