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Artificial Intelligence (2342) Obstetrics, Gynecology, and Reproductive Medicine (343) Decision Support for Health Professionals (1635) Development and Evaluation of Research Methods, Instruments and Tools (807) Imaging Informatics (329) Machine Learning (2228)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52637, first published .
Evaluation of the Clinical Efficacy and Trust in AI-Assisted Embryo Ranking: Survey-Based Prospective Study

Evaluation of the Clinical Efficacy and Trust in AI-Assisted Embryo Ranking: Survey-Based Prospective Study

Evaluation of the Clinical Efficacy and Trust in AI-Assisted Embryo Ranking: Survey-Based Prospective Study

Authors of this article:

Hyung Min Kim1 Author Orcid Image ;   Hyoeun Kang1 Author Orcid Image ;   Chaeyoon Lee1 Author Orcid Image ;   Jong Hyuk Park2 Author Orcid Image ;   Mi Kyung Chung3 Author Orcid Image ;   Miran Kim4 Author Orcid Image ;   Na Young Kim5 Author Orcid Image ;   Hye Jun Lee6 Author Orcid Image
Article Authors Cited by (14) Tweetations (3) Metrics

Journals

  1. Sergeev S, Diakova I, Nadirashvili L. Neural networks pipeline for quality management in IVF laboratory. Journal of IVF-Worldwide 2024;2(4) View
  2. Shoham Z. Can Elective Single Embryo Transfer (eSET) with AI Integration Become the Future of IVF?. Journal of IVF-Worldwide 2025;3(1) View
  3. Zhong J, Zhu T, Huang Y. Reporting Quality of AI Intervention in Randomized Controlled Trials in Primary Care: Systematic Review and Meta-Epidemiological Study. Journal of Medical Internet Research 2025;27:e56774 View
  4. Fee N, Glover L, Bauman R, Crosby D. Patient perceptions on the use of artificial intelligence (AI) in fertility treatment. Human Fertility 2025;28(1) View
  5. Dańczak M. Sztuczna inteligencja w procedurze in vitro – dylematy etyczne i stanowisko Kościoła katolickiego. Teologia i Moralność 2025;20(1(38)) View
  6. Mrugacz G, Mospinek A, Jagielska M, Miszczak D, Matosek A, Ducher-Hanaka M, Gustaw P, Januszewska K, Grzegorczyk A, Pekar S. Artificial Intelligence in Routine IVF Practice. Biology 2025;15(1):42 View
  7. Gozum I. Conscience, Care, and Code: Moral Theology, AI, and Ethical Decision-Making at the Thresholds of Life. Journal of Religion and Health 2026 View
  8. Choudhury A, Shamszare H. Human Factors Influencing Trust in Healthcare Artificial Intelligence: Systematic Literature Review. IISE Transactions on Occupational Ergonomics and Human Factors 2026:1 View
  9. Nigmatova N, Sergeev S, Buyanzhargal Y, Kaldarbekova B, Arstanbayeva G, Azimkhan M, Khonik N, Makisheva A, Shchigolev V. Comprehensive assessment of pronuclear morphological pattern prognostic value using machine learning approaches in IVF programs. Journal of IVF-Worldwide 2026;4(1) View
  10. Jonaitis D, Raudonis V, Drejeriene E, Kozlovskaja-Gumbriene A, Salumets A. Soft Optical Sensor for Embryo Quality Evaluation Based on Multi-Focal Image Fusion and RAG-Enhanced Vision Transformers. Sensors 2026;26(5):1441 View
  11. Kakulavarapu R, Delbarre E, Sharma A, Jahanlu D, Riegler M, Haugen T, Iliceto M, Stensen M. Investigating discrepancies in accuracy, agreement and interpretability for single-frame embryo classification tasks conducted by embryologists and deep learning models. Frontiers in Reproductive Health 2026;8 View
  12. Jeong M, Park K, Jung D, Shin S, Lee J, Ko J, Bang S, Ahn J. Recent Advances in Sex-Specific Reproductive Microphysiological Systems for the Systematic Evaluation of Assisted Reproductive Technology. Materials Today Bio 2026:103050 View

Conference Proceedings

  1. Benfettoume Souda A, Bechar M, Hamza-Cherif S, Guyader J, Elbouz M, Morel F, Perrin A, Settouti N. Proceedings of the IEEE/ACM 12th International Conference on Big Data Computing, Applications and Technologies. Scaling AI for Embryo Transition Detection: Benchmarking Spatio-Temporal Deep Models View
  2. Kalaskar G, More A, Choudhary N, Padwal L, Gedekar P, Khan M. 2025 3rd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry (IDICAIHEI). Artificial Intelligence-Based Quantification of Cytoplasmic Fragmentation in Blastocyst-Stage Embryos Following Intracytoplasmic Sperm Injection as a Predictor of Implantation and Clinical Pregnancy Outcomes View