IVF procedures can be improved by combining genetic and clinical data to predict the number of eggs retrieved in patients undergoing ovarian stimulation.
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Article URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011020
Article Title: Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
Author Countries : Poland
Funding: The research was co-financed by the European Regional Development Fund under the Pomorskie Voivodeship Regional Operational Programme for 2014-2020 as part of the project: The Development and Implementation of a New Method for Diagnosing Fertility Disorders of Genetic Origin Based on Next-generation High-throughput Sequencing. Co-financing agreement No. RPPM.01.01.01-22-0060/17. The funders had no role in study design, data collection or analysis, the decision to publish, or the preparation of the manuscript.
PLOS Computational Biology
Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
27-Apr-2023
I have read the journal’s policy and the authors of this manuscript have the following competing interests: KZ, SP, MM, MK, DD, DD, and JJ-B are employees of INVICTA, clinics and medical laboratories for infertility treatment. PW and MZ are employees of MIM Solutions. The affiliation does not affect the authors’ impartiality, adherence to journal standards and policies, or availability of data. AK declares no conflict of interest.