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<div><p>Aim of the study</p><p>The aim was to systematically review the literature and perform a meta-analysis to estimate the performance of artificial intelligence (AI) algorithms in detecting meniscal injuries.</p><p>Materials and methods</p><p>A sy...

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Bibliographic Details
Main Author:	Soheil Mohammadi (12468952) (author)
Other Authors:	Ali Jahanshahi (5231792) (author), Mohammad Shahrabi Farahani (19126660) (author), Mohammad Amin Salehi (12468949) (author), Negin Frounchi (17264950) (author), Ali Guermazi (4002773) (author)
Published:	2025
Subjects:	Biotechnology Cancer Science Policy Biological Sciences not elsewhere classified transfer learning usage multivariable prediction model mostly expert radiologists external test set cochrane central databases 92 contingency tables probast ), respectively 92 ), respectively lower diagnostic performance bias assessment tool studies validating algorithms 91 ), xlink "> transparent reporting systematically review systematic search systematic review surgical reports study imply reporting quality reference standard meniscal tear main outcome internal validation individual prognosis imaging view ieee xplore following variables evaluated using data augmentation confidence interval based algorithms artificial intelligence 15 studies
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