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Jonas E Malmsten

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

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F&S Science|October 11, 2023
Embryo ranking agreement between embryologists and artificial intelligence algorithmsNikica Zaninovic, Jose T Sierra, Jonas E Malmsten, et al.
Fertility and Sterility|November 15, 2022
Pregnancy outcomes after oral and injectable ovulation induction in women with infertility with a low antimüllerian hormone level compared with those with a normal antimüllerian hormone levelPhillip A Romanski, Pietro Bortoletto, Jonas E Malmsten, et al.
NPJ Digital Medicine|April 23, 2026
Trial emulation for validating the clinical efficacy of a foundational AI model in embryo selectionSuraj Rajendran, Jonas E Malmsten, Lorena B Arnal, et al.
Nature Communications|July 11, 2025
A foundational model for in vitro fertilization trained on 18 million time-lapse imagesSuraj Rajendran, Eeshaan Rehani, William Phu, et al.
Fertility and Sterility|August 28, 2025
Stability and Reliability of Artificial Intelligence Models in Embryo Selection for In-Vitro FertilizationPrudhvi Thirumalaraju, Manoj Kumar Kanakasabapathy, Hemanth Kandula, et al.
Fertility and Sterility|January 9, 2022
Characterization of an artificial intelligence model for ranking static images of blastocyst stage embryosKevin Loewke, Justina Hyunjii Cho, Camelia D Brumar, et al.
NPJ Digital Medicine|July 16, 2019
Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilizationPegah Khosravi, Ehsan Kazemi, Qiansheng Zhan, et al.
Biorxiv : the Preprint Server for Biology|September 11, 2023
Automatic Ploidy Prediction and Quality Assessment of Human Blastocyst Using Time-Lapse ImagingSuraj Rajendran, Matthew Brendel, Josue Barnes, et al.
Nature Communications|September 5, 2024
Automatic ploidy prediction and quality assessment of human blastocysts using time-lapse imagingSuraj Rajendran, Matthew Brendel, Josue Barnes, et al.
The Lancet. Digital Health|December 21, 2022
A non-invasive artificial intelligence approach for the prediction of human blastocyst ploidy: a retrospective model development and validation studyJosue Barnes, Matthew Brendel, Vianne R Gao, et al.
Pageof 1

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

Sort By:
Pageof 1
F&S Science|October 11, 2023
Embryo ranking agreement between embryologists and artificial intelligence algorithmsNikica Zaninovic, Jose T Sierra, Jonas E Malmsten, et al.
Fertility and Sterility|November 15, 2022
Pregnancy outcomes after oral and injectable ovulation induction in women with infertility with a low antimüllerian hormone level compared with those with a normal antimüllerian hormone levelPhillip A Romanski, Pietro Bortoletto, Jonas E Malmsten, et al.
NPJ Digital Medicine|April 23, 2026
Trial emulation for validating the clinical efficacy of a foundational AI model in embryo selectionSuraj Rajendran, Jonas E Malmsten, Lorena B Arnal, et al.
Nature Communications|July 11, 2025
A foundational model for in vitro fertilization trained on 18 million time-lapse imagesSuraj Rajendran, Eeshaan Rehani, William Phu, et al.
Fertility and Sterility|August 28, 2025
Stability and Reliability of Artificial Intelligence Models in Embryo Selection for In-Vitro FertilizationPrudhvi Thirumalaraju, Manoj Kumar Kanakasabapathy, Hemanth Kandula, et al.
Fertility and Sterility|January 9, 2022
Characterization of an artificial intelligence model for ranking static images of blastocyst stage embryosKevin Loewke, Justina Hyunjii Cho, Camelia D Brumar, et al.
NPJ Digital Medicine|July 16, 2019
Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilizationPegah Khosravi, Ehsan Kazemi, Qiansheng Zhan, et al.
Biorxiv : the Preprint Server for Biology|September 11, 2023
Automatic Ploidy Prediction and Quality Assessment of Human Blastocyst Using Time-Lapse ImagingSuraj Rajendran, Matthew Brendel, Josue Barnes, et al.
Nature Communications|September 5, 2024
Automatic ploidy prediction and quality assessment of human blastocysts using time-lapse imagingSuraj Rajendran, Matthew Brendel, Josue Barnes, et al.
The Lancet. Digital Health|December 21, 2022
A non-invasive artificial intelligence approach for the prediction of human blastocyst ploidy: a retrospective model development and validation studyJosue Barnes, Matthew Brendel, Vianne R Gao, et al.
Pageof 1