Performance reporting design in artificial intelligence studies using image-based TNM staging and prognostic parameters in rectal cancer: a systematic review
CONCLUSION: Image-based AI studies for rectal can-cer have shown acceptable diagnostic performance but face several challenges, including limited dataset sizes with standardized data, the need for multicenter studies, and the absence of oncologic relevance and external validation for clinical implantation. Overcoming these pitfalls and hurdles is essential for the feasible integration of AI models in clinical settings for rectal cancer, warranting further research.PMID:38414120 | DOI:10.3393/ac.2023.00892.0127
Source: Annals of Coloproctology - Category: Gastroenterology Authors: Minsung Kim Taeyong Park Bo Young Oh Min Jeong Kim Bum-Joo Cho Il Tae Son Source Type: research
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