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by claude@2026-07, 2026-07-14
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This report describes Version 1.0 of the Assisted Reproductive Technology (ART) Dataset, a private collection of 14,776 embryo time-lapse images and electronic health records from 2,500 treatments to aid machine learning model development.
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by claude@2026-07, 2026-07-14
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This paper presents Version 1.0 of the Assisted Reproductive Technology (ART) Dataset, compiled from treatments at an ART fertility clinic in Abu Dhabi, UAE, between 2015 and 2022, including electronic health record data and embryo development time-lapse image sequences from a Vitrolife EmbryoScope. The authors report a processed dataset of 14,776 embryos from 1,810 patients across 2,500 treatments and describe the extraction and pre-processing pipelines used for both image and EHR modalities. The dataset is private and only available to collaborators in the UAE after reasonable request and ethical approval, which the authors note by publishing the report mainly for transparency of methodology rather than providing direct access. This paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.
Abstract
In this report, we present Version 1.0 of the Assisted Reproductive Technology (ART) Dataset, a multi-modal fertility dataset from treatments performed at the ART Fertility Clinic in Abu Dhabi, United Arab Emirates, between 2015 and 2022. The data consists of Electronic Health Records (EHR) and embryo development image sequences captured with the Vitrolife EmbryoScope time-lapse system, providing detailed treatment, morphology, and pregnancy outcome information. The final processed dataset consists of a total of 14,776 embryos from 1,810 patients across 2,500 treatments. This dataset will be used in the development of machine learning models for automated analysis of embryo development and viability, to assist clinical decision-making. This report provides a summary of the statistics of the dataset, as well as the extraction and pre-processing pipelines of the time-lapse images and EHR data. The dataset is private, so we publish this report for transparency on data pre-processing pipelines to share the methodology with similar studies that may arise.
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Abstract
In this report, we present Version 1.0 of the Assisted Reproductive Technology (ART) Dataset, a multi-modal fertility dataset from treatments performed at the ART Fertility Clinic in Abu Dhabi, United Arab Emirates, between 2015 and 2022. The data consists of Electronic Health Records (EHR) and embryo development image sequences captured with the Vitrolife EmbryoScope time-lapse system, providing detailed treatment, morphology, and pregnancy outcome information. The final processed dataset consists of a total of 14,776 embryos from 1,810 patients across 2,500 treatments. This dataset will be used in the development of machine learning models for automated analysis of embryo development and viability, to assist clinical decision-making. This report provides a summary of the statistics of the dataset, as well as the extraction and pre-processing pipelines of the time-lapse images and EHR data. The dataset is private, so we publish this report for transparency on data pre-processing pipelines to share the methodology with similar studies that may arise.
Competing Interest Statement
The authors have declared no competing interest.
Funding Statement
This study did not receive any funding
Author Declarations
I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.
Yes
The details of the IRB/oversight body that provided approval or exemption for the research described are given below:
IRB of NYU Abu Dhabi gave ethical approval for this work Ethics committee of ART Fertility Clinics gave ethical approval for this work
I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.
Yes
I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).
Yes
I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.
Yes
Footnotes
↵* Co-first authors.
Correction of co-author last name
Data Availability
Data presented in the study is private and can only be made available to collaborators in the UAE, due to local regulation, upon reasonable request and ethical approval
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