@inproceedings{caa8a4a32ca444bea3c03047b4850fb4,
title = "Multimodal Learning for Embryo Viability Prediction in Clinical IVF",
abstract = "In clinical In-Vitro Fertilization (IVF), identifying the most viable embryo for transfer is important to increasing the likelihood of a successful pregnancy. Traditionally, this process involves embryologists manually assessing embryos{\textquoteright} static morphological features at specific intervals using light microscopy. This manual evaluation is not only time-intensive and costly, due to the need for expert analysis, but also inherently subjective, leading to variability in the selection process. To address these challenges, we develop a multimodal model that leverages both time-lapse video data and Electronic Health Records (EHRs) to predict embryo viability. One of the primary challenges of our research is to effectively combine time-lapse video and EHR data, owing to their inherent differences in modality. We comprehensively analyze our multimodal model with various modality inputs and integration approaches. Our approach will enable fast and automated embryo viability predictions in scale for clinical IVF.",
keywords = "EHR, Human Embryos, In-Vitro Fertilization, Multimodal Learning, Time-lapse Video",
author = "Junsik Kim and Zhiyi Shi and Davin Jeong and Johannes Knittel and Yang, {Helen Y.} and Yonghyun Song and Wanhua Li and Yicong Li and Dalit Ben-Yosef and Daniel Needleman and Hanspeter Pfister",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; 27th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2024 ; Conference date: 06-10-2024 Through 10-10-2024",
year = "2024",
doi = "10.1007/978-3-031-72086-4_51",
language = "אנגלית",
isbn = "9783031720857",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "542--552",
editor = "Linguraru, {Marius George} and Qi Dou and Aasa Feragen and Stamatia Giannarou and Ben Glocker and Karim Lekadir and Schnabel, {Julia A.}",
booktitle = "Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 - 27th International Conference, Proceedings",
address = "גרמניה",
}