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Development and validation of an artificial intelligence assisted prenatal ultrasonography screening system for trainees.
Lei T, Feng JL, Lin MF, Xie BH, Zhou Q, Wang N, Zheng Q, Yang YD, Guo HM, Xie HN. Lei T, et al. Int J Gynaecol Obstet. 2024 Apr;165(1):306-317. doi: 10.1002/ijgo.15167. Epub 2023 Oct 4. Int J Gynaecol Obstet. 2024. PMID: 37789758
We aimed to develop and validate a prenatal-screening artificial intelligence system (PSAIS) for real-time evaluation of the quality of anatomical images, indicating existing and missing structures. METHODS: Still ultrasonographic images obtained from fetuses of 18-32 week …
We aimed to develop and validate a prenatal-screening artificial intelligence system (PSAIS) for real-time evaluation of the quality …
Enhancing trainee performance in obstetric ultrasound through an artificial intelligence system: randomized controlled trial.
Lei T, Zheng Q, Feng J, Zhang L, Zhou Q, He M, Lin M, Xie HN. Lei T, et al. Ultrasound Obstet Gynecol. 2024 Oct;64(4):453-462. doi: 10.1002/uog.29101. Epub 2024 Sep 17. Ultrasound Obstet Gynecol. 2024. PMID: 39289903 Clinical Trial.
Secondary outcomes included the expert ratings of the image quality in each trainee's end-of-cycle test and the discordance between ratings by trainees and the expert. ...In both groups, the discordance between trainees' ratings of the quality of their own images an …
Secondary outcomes included the expert ratings of the image quality in each trainee's end-of-cycle test and the discordance between r …