| Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization P Khosravi, E Kazemi, Q Zhan, JE Malmsten, M Toschi, P Zisimopoulos, ... NPJ digital medicine 2 (1), 21, 2019 | 229 | 2019 |
| Blastocyst score, a blastocyst quality ranking tool, is a predictor of blastocyst ploidy and implantation potential Q Zhan, ET Sierra, J Malmsten, Z Ye, Z Rosenwaks, N Zaninovic F&S Reports 1 (2), 133-141, 2020 | 29 | 2020 |
| Predictive modeling in reproductive medicine: where will the future of artificial intelligence research take us? CL Curchoe, J Malmsten, C Bormann, H Shafiee, AFS Farias, ... Fertility and sterility 114 (5), 934-940, 2020 | 27 | 2020 |
| Comparing TensorFlow deep learning performance using CPUs, GPUs, local PCs and cloud J Lawrence, J Malmsten, A Rybka, DA Sabol, K Triplin | 27 | 2017 |
| Robust automated assessment of human blastocyst quality using deep learning P Khosravi, E Kazemi, Q Zhan, M Toschi, JE Malmsten, C Hickman, ... BioRxiv, 394882, 2018 | 19 | 2018 |
| Characterization of an artificial intelligence model for ranking static images of blastocyst stage embryos K Loewke, JH Cho, CD Brumar, P Maeder-York, O Barash, JE Malmsten, ... Fertility and Sterility 117 (3), 528-535, 2022 | 14 | 2022 |
| Automated cell division classification in early mouse and human embryos using convolutional neural networks J Malmsten, N Zaninovic, Q Zhan, Z Rosenwaks, J Shan Neural Computing and Applications 33, 2217-2228, 2021 | 12 | 2021 |
| Application of artificial intelligence technology to increase the efficacy of embryo selection and prediction of live birth using human blastocysts cultured in a time-lapse … N Zaninovic, CJ Rocha, Q Zhan, M Toschi, J Malmsten, M Nogueira, ... Fertility and Sterility 110 (4), e372-e373, 2018 | 11 | 2018 |
| Assessing human blastocyst quality using artificial intelligence (AI) convolutional neural network (CNN) N Zaninovic, P Khosravi, I Hajirasouliha, JE Malmsten, E Kazemi, Q Zhan, ... Fertility and Sterility 110 (4), e89, 2018 | 10 | 2018 |
| Automatic prediction of embryo cell stages using artificial intelligence convolutional neural network J Malmsten, N Zaninovic, Q Zhan, M Toschi, Z Rosenwaks, J Shan Fertility and Sterility 110 (4), e360, 2018 | 8 | 2018 |
| Automated cell stage predictions in early mouse and human embryos using convolutional neural networks J Malmsten, N Zaninovic, Q Zhan, Z Rosenwaks, J Shan 2019 IEEE EMBS international conference on biomedical & health informatics …, 2019 | 7 | 2019 |
| Noninvasive detection of blastocyst ploidy (euploid vs. aneuploid) using artificial intelligence (AI) with deep learning methods J Barnes, J Malmsten, Q Zhan, I Hajirasouliha, O Elemento, J Sierra, ... Fertility and Sterility 114 (3), e76, 2020 | 6 | 2020 |
| Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization. npj Digital Medicine, 2 (1): 21, 12 2019 P Khosravi, E Kazemi, Q Zhan, JE Malmsten, M Toschi, P Zisimopoulos, ... ISSN, 2019 | 5 | 2019 |
| Artificial intelligence assessment of time-lapse images can predict with 77% accuracy whether a human embryo capable of achieving a pregnancy will miscarry R Hariharan, P He, M Meseguer, M Toschi, JC Rocha, N Zaninovic, ... Fertility and Sterility 112 (3), e38-e39, 2019 | 4 | 2019 |
| A non-invasive artificial intelligence approach for the prediction of human blastocyst ploidy: a retrospective model development and validation study J Barnes, M Brendel, VR Gao, S Rajendran, J Kim, Q Li, JE Malmsten, ... The Lancet Digital Health 5 (1), e28-e40, 2023 | 1 | 2023 |
| Pregnancy outcomes after oral and injectable ovulation induction in women with infertility with a low antimüllerian hormone level compared with those with a normal … PA Romanski, P Bortoletto, JE Malmsten, KS Tan, SD Spandorfer Fertility and Sterility 118 (6), 1048-1056, 2022 | 1 | 2022 |
| P-588 Evaluation of anti-Müllerian hormone levels as a predictor of pregnancy outcome following intrauterine insemination in infertile women P Romanski, P Bortoletto, J Malmsten, S Spandorfer Human Reproduction 37 (Supplement_1), deac107. 542, 2022 | 1 | 2022 |
| O-120 Embryo ranking agreement between embryologists and AI algorithms N Zaninovic, J Sierra, J Malmsten, Z Rosenwaks Human Reproduction 37 (Supplement_1), deac105. 020, 2022 | 1 | 2022 |
| Machine learning for automated cell segmentation in embryos P He, R Hariharan, J Chambost, C Jacques, R Azambuja, M Badalotti, ... HUMAN REPRODUCTION 36, 211-211, 2021 | 1 | 2021 |
| Perinatal outcome using time-lapse system and reduced oxygen culture in IVF patients N Zaninovic, Q Zhan, R Clarke, Z Ye, J Malmsten, Z Rosenwaks Fertility and Sterility 104 (3), e227-e228, 2015 | 1 | 2015 |
