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Jørgen Berntsen

Showing results (1-10 of 17) with videos related to

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Reproductive Biomedicine Online|November 1, 2023
Improved pregnancy prediction performance in an updated deep-learning embryo selection model: a retrospective independent validation studySatoshi Ueno, Jørgen Berntsen, Tadashi Okimura, et al.
Computers in Biology and Medicine|October 21, 2019
Automatic grading of human blastocysts from time-lapse imagingMikkel F Kragh, Jens Rimestad, Jørgen Berntsen, et al.
Journal of Assisted Reproduction and Genetics|July 26, 2022
Correlation between an annotation-free embryo scoring system based on deep learning and live birth/neonatal outcomes after single vitrified-warmed blastocyst transfer: a single-centre, large-cohort retrospective studySatoshi Ueno, Jørgen Berntsen, Motoki Ito, et al.
Plos One|February 2, 2022
Robust and generalizable embryo selection based on artificial intelligence and time-lapse image sequencesJørgen Berntsen, Jens Rimestad, Jacob Theilgaard Lassen, et al.
Human Reproduction (Oxford, England)|June 13, 2025
Predicting time to live birth with deep learning embryo ranking: a novel multiple imputation approachLorena Bori, Martin Nygård Johansen, Jørgen Berntsen, et al.
Reproductive Biomedicine Online|October 16, 2008
Symposium: innovative techniques in human embryo viability assessment. Human oocyte respiration-rate measurement--potential to improve oocyte and embryo selection?Lynette Scott, Jørgen Berntsen, Darlene Davies, et al.
Reproductive Biomedicine Online|December 5, 2022
Does embryo categorization by existing artificial intelligence, morphokinetic or morphological embryo selection models correlate with blastocyst euploidy rates?Keiichi Kato, Satoshi Ueno, Jørgen Berntsen, et al.
Scientific Reports|March 15, 2023
Development and validation of deep learning based embryo selection across multiple days of transferJacob Theilgaard Lassen, Mikkel Fly Kragh, Jens Rimestad, et al.
Fertility and Sterility|July 11, 2021
Pregnancy prediction performance of an annotation-free embryo scoring system on the basis of deep learning after single vitrified-warmed blastocyst transfer: a single-center large cohort retrospective studySatoshi Ueno, Jørgen Berntsen, Motoki Ito, et al.
F&S Reports|June 22, 2026
Embryologist experience affects concordance with an artificial intelligence embryo ranking algorithm: benefit of artificial intelligence assistanceJørgen Berntsen, Philip Marsh, Brendan Burkart, et al.
Pageof 2

Showing results (1-10 of 17) with videos related to

Sort By:
Pageof 2
Reproductive Biomedicine Online|November 1, 2023
Improved pregnancy prediction performance in an updated deep-learning embryo selection model: a retrospective independent validation studySatoshi Ueno, Jørgen Berntsen, Tadashi Okimura, et al.
Computers in Biology and Medicine|October 21, 2019
Automatic grading of human blastocysts from time-lapse imagingMikkel F Kragh, Jens Rimestad, Jørgen Berntsen, et al.
Journal of Assisted Reproduction and Genetics|July 26, 2022
Correlation between an annotation-free embryo scoring system based on deep learning and live birth/neonatal outcomes after single vitrified-warmed blastocyst transfer: a single-centre, large-cohort retrospective studySatoshi Ueno, Jørgen Berntsen, Motoki Ito, et al.
Plos One|February 2, 2022
Robust and generalizable embryo selection based on artificial intelligence and time-lapse image sequencesJørgen Berntsen, Jens Rimestad, Jacob Theilgaard Lassen, et al.
Human Reproduction (Oxford, England)|June 13, 2025
Predicting time to live birth with deep learning embryo ranking: a novel multiple imputation approachLorena Bori, Martin Nygård Johansen, Jørgen Berntsen, et al.
Reproductive Biomedicine Online|October 16, 2008
Symposium: innovative techniques in human embryo viability assessment. Human oocyte respiration-rate measurement--potential to improve oocyte and embryo selection?Lynette Scott, Jørgen Berntsen, Darlene Davies, et al.
Reproductive Biomedicine Online|December 5, 2022
Does embryo categorization by existing artificial intelligence, morphokinetic or morphological embryo selection models correlate with blastocyst euploidy rates?Keiichi Kato, Satoshi Ueno, Jørgen Berntsen, et al.
Scientific Reports|March 15, 2023
Development and validation of deep learning based embryo selection across multiple days of transferJacob Theilgaard Lassen, Mikkel Fly Kragh, Jens Rimestad, et al.
Fertility and Sterility|July 11, 2021
Pregnancy prediction performance of an annotation-free embryo scoring system on the basis of deep learning after single vitrified-warmed blastocyst transfer: a single-center large cohort retrospective studySatoshi Ueno, Jørgen Berntsen, Motoki Ito, et al.
F&S Reports|June 22, 2026
Embryologist experience affects concordance with an artificial intelligence embryo ranking algorithm: benefit of artificial intelligence assistanceJørgen Berntsen, Philip Marsh, Brendan Burkart, et al.
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