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Journal Abstract Search

671 related items for PubMed ID: 35944167

  • 1. Embryologist agreement when assessing blastocyst implantation probability: is data-driven prediction the solution to embryo assessment subjectivity?
    Fordham DE, Rosentraub D, Polsky AL, Aviram T, Wolf Y, Perl O, Devir A, Rosentraub S, Silver DH, Gold Zamir Y, Bronstein AM, Lara Lara M, Ben Nagi J, Alvarez A, Munné S.
    Hum Reprod; 2022 Sep 30; 37(10):2275-2290. PubMed ID: 35944167
    [Abstract] [Full Text] [Related]

  • 2. Discard or not discard, that is the question: an international survey across 117 embryologists on the clinical management of borderline quality blastocysts.
    Chiappetta V, Innocenti F, Coticchio G, Ahlström A, Albricci L, Badajoz V, Hebles M, Gallardo M, Benini F, Canosa S, Kumpošt J, Milton K, Montanino Oliva D, Maggiulli R, Rienzi L, Cimadomo D.
    Hum Reprod; 2023 Oct 03; 38(10):1901-1909. PubMed ID: 37649342
    [Abstract] [Full Text] [Related]

  • 3. Development of an artificial intelligence-based assessment model for prediction of embryo viability using static images captured by optical light microscopy during IVF.
    VerMilyea M, Hall JMM, Diakiw SM, Johnston A, Nguyen T, Perugini D, Miller A, Picou A, Murphy AP, Perugini M.
    Hum Reprod; 2020 Apr 28; 35(4):770-784. PubMed ID: 32240301
    [Abstract] [Full Text] [Related]

  • 4. Should we freeze it? Agreement on fate of borderline blastocysts is poor and does not improve with a modified blastocyst grading system.
    Hammond ER, Foong AKM, Rosli N, Morbeck DE.
    Hum Reprod; 2020 May 01; 35(5):1045-1053. PubMed ID: 32358601
    [Abstract] [Full Text] [Related]

  • 5. Development of an artificial intelligence model for predicting the likelihood of human embryo euploidy based on blastocyst images from multiple imaging systems during IVF.
    Diakiw SM, Hall JMM, VerMilyea MD, Amin J, Aizpurua J, Giardini L, Briones YG, Lim AYX, Dakka MA, Nguyen TV, Perugini D, Perugini M.
    Hum Reprod; 2022 Jul 30; 37(8):1746-1759. PubMed ID: 35674312
    [Abstract] [Full Text] [Related]

  • 6. Clinical validation of an automatic classification algorithm applied on cleavage stage embryos: analysis for blastulation, euploidy, implantation, and live-birth potential.
    Valera MA, Aparicio-Ruiz B, Pérez-Albalá S, Romany L, Remohí J, Meseguer M.
    Hum Reprod; 2023 Jun 01; 38(6):1060-1075. PubMed ID: 37018626
    [Abstract] [Full Text] [Related]

  • 7. BlastAssist: a deep learning pipeline to measure interpretable features of human embryos.
    Yang HY, Leahy BD, Jang WD, Wei D, Kalma Y, Rahav R, Carmon A, Kopel R, Azem F, Venturas M, Kelleher CP, Cam L, Pfister H, Needleman DJ, Ben-Yosef D.
    Hum Reprod; 2024 Apr 03; 39(4):698-708. PubMed ID: 38396213
    [Abstract] [Full Text] [Related]

  • 8. A hybrid artificial intelligence model leverages multi-centric clinical data to improve fetal heart rate pregnancy prediction across time-lapse systems.
    Duval A, Nogueira D, Dissler N, Maskani Filali M, Delestro Matos F, Chansel-Debordeaux L, Ferrer-Buitrago M, Ferrer E, Antequera V, Ruiz-Jorro M, Papaxanthos A, Ouchchane H, Keppi B, Prima PY, Regnier-Vigouroux G, Trebesses L, Geoffroy-Siraudin C, Zaragoza S, Scalici E, Sanguinet P, Cassagnard N, Ozanon C, De La Fuente A, Gómez E, Gervoise Boyer M, Boyer P, Ricciarelli E, Pollet-Villard X, Boussommier-Calleja A.
    Hum Reprod; 2023 Apr 03; 38(4):596-608. PubMed ID: 36763673
    [Abstract] [Full Text] [Related]

  • 9. Inter-observer and intra-observer agreement between embryologists during selection of a single Day 5 embryo for transfer: a multicenter study.
    Storr A, Venetis CA, Cooke S, Kilani S, Ledger W.
    Hum Reprod; 2017 Feb 03; 32(2):307-314. PubMed ID: 28031323
    [Abstract] [Full Text] [Related]

  • 10. Embryo selection through artificial intelligence versus embryologists: a systematic review.
    Salih M, Austin C, Warty RR, Tiktin C, Rolnik DL, Momeni M, Rezatofighi H, Reddy S, Smith V, Vollenhoven B, Horta F.
    Hum Reprod Open; 2023 Feb 03; 2023(3):hoad031. PubMed ID: 37588797
    [Abstract] [Full Text] [Related]

  • 11. Generative artificial intelligence to produce high-fidelity blastocyst-stage embryo images.
    Cao P, Derhaag J, Coonen E, Brunner H, Acharya G, Salumets A, Zamani Esteki M.
    Hum Reprod; 2024 Jun 03; 39(6):1197-1207. PubMed ID: 38600621
    [Abstract] [Full Text] [Related]

  • 12. Testing an artificial intelligence algorithm to predict fetal heartbeat of vitrified-warmed blastocysts from a single image: predictive ability in different settings.
    Conversa L, Bori L, Insua F, Marqueño S, Cobo A, Meseguer M.
    Hum Reprod; 2024 Oct 01; 39(10):2240-2248. PubMed ID: 39173597
    [Abstract] [Full Text] [Related]

  • 13. Prospective study of automated versus manual annotation of early time-lapse markers in the human preimplantation embryo.
    Kaser DJ, Farland LV, Missmer SA, Racowsky C.
    Hum Reprod; 2017 Aug 01; 32(8):1604-1611. PubMed ID: 28854587
    [Abstract] [Full Text] [Related]

  • 14. The higher the score, the better the clinical outcome: retrospective evaluation of automatic embryo grading as a support tool for embryo selection in IVF laboratories.
    Bori L, Meseguer F, Valera MA, Galan A, Remohi J, Meseguer M.
    Hum Reprod; 2022 May 30; 37(6):1148-1160. PubMed ID: 35435210
    [Abstract] [Full Text] [Related]

  • 15. A comparison of morphokinetic models and morphological selection for prioritizing euploid embryos: a multicentre cohort study.
    Bamford T, Smith R, Young S, Evans A, Lockwood M, Easter C, Montgomery S, Barrie A, Dhillon-Smith R, Coomarasamy A, Campbell A.
    Hum Reprod; 2024 Jan 05; 39(1):53-61. PubMed ID: 37963011
    [Abstract] [Full Text] [Related]

  • 16. Deep learning as a predictive tool for fetal heart pregnancy following time-lapse incubation and blastocyst transfer.
    Tran D, Cooke S, Illingworth PJ, Gardner DK.
    Hum Reprod; 2019 Jun 04; 34(6):1011-1018. PubMed ID: 31111884
    [Abstract] [Full Text] [Related]

  • 17. Performance of a deep learning based neural network in the selection of human blastocysts for implantation.
    Bormann CL, Kanakasabapathy MK, Thirumalaraju P, Gupta R, Pooniwala R, Kandula H, Hariton E, Souter I, Dimitriadis I, Ramirez LB, Curchoe CL, Swain J, Boehnlein LM, Shafiee H.
    Elife; 2020 Sep 15; 9():. PubMed ID: 32930094
    [Abstract] [Full Text] [Related]

  • 18. Correlation between standard blastocyst morphology, euploidy and implantation: an observational study in two centers involving 956 screened blastocysts.
    Capalbo A, Rienzi L, Cimadomo D, Maggiulli R, Elliott T, Wright G, Nagy ZP, Ubaldi FM.
    Hum Reprod; 2014 Jun 15; 29(6):1173-81. PubMed ID: 24578475
    [Abstract] [Full Text] [Related]

  • 19. Development of a generally applicable morphokinetic algorithm capable of predicting the implantation potential of embryos transferred on Day 3.
    Petersen BM, Boel M, Montag M, Gardner DK.
    Hum Reprod; 2016 Oct 15; 31(10):2231-44. PubMed ID: 27609980
    [Abstract] [Full Text] [Related]

  • 20. Cytoplasmic strings in human blastocysts: hypotheses of their role and implications for embryo selection.
    Marconetto A, Innocenti F, Saturno G, Taggi M, Chiappetta V, Trio S, De Falco F, Albricci L, Coticchio G, Ahlström A, Fiorentino G, Maggiulli R, Vaiarelli A, Zuccotti M, Rienzi L, Cimadomo D.
    Hum Reprod; 2024 Nov 01; 39(11):2453-2465. PubMed ID: 39354750
    [Abstract] [Full Text] [Related]

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