MAIA platform for routine clinical testing: an artificial intelligence embryo selection tool developed to assist embryologists

The need to reduce the number of embryos transferred in assisted reproductive care to prevent multiple gestations has led to a stronger emphasis on selecting embryos with the highest morphological quality. Although this evaluation has traditionally been performed by trained embryologists, the increasing use of time-lapse incubators has introduced a greater volume of data and subjectivity in decision-making. Artificial intelligence (AI)-based tools can support embryologists by offering objective, standardized embryo assessments.In Brazil, like other countries, where imported embryo selection technologies may not account for local demographic and ethnic profiles, an AI model - Morphological Artificial Intelligence Assistance (MAIA) - was developed through a collaboration between a university and a private fertility clinic in São Paulo. The model was trained using 1,015 embryo images and prospectively tested in a clinical setting on 200 single embryo transfers. In clinical testing, MAIA achieved an overall accuracy of 66.5%. In elective embryo transfers, where there were more than one embryo eligible for transfer, MAIA achieved 70.1% accuracy for predicting clinical pregnancy. Designed with a user-friendly interface tailored by embryologists, MAIA provides real-time embryo evaluations to support decision-making in routine care.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-09-01
DOI
https://doi.org/10.1038/s41598-025-17755-y
Citations
2
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
1.31

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

MAIA platform for routine clinical testing: an artificial intelligence embryo selection tool developed to assist embryologists

J.R. Alegretti, Marcelo Barbanti Duarte, Bruno Mendes, Dóris Spinosa Chéles et al.
2 citations
Scientific Reports
Artificial Intelligence in Healthcare and Education
1.31
article

MAIA platform for routine clinical testing: an artificial intelligence embryo selection tool developed to assist embryologists

J.R. Alegretti, Marcelo Barbanti Duarte, Bruno Mendes, Dóris Spinosa Chéles, Bárbara Hatzlhoffer Lourenço, Aline R. Lorenzon, Marcelo Fábio Gouveia Nogueira, Mariana Nicolielo, Viviana Carolina Oyan de Moraes, José Celso Rocha, Maurício B. Chehin, Mattia Maffeis, Catherine Kuhn Jacobs
article en
2 citations

Abstract

The need to reduce the number of embryos transferred in assisted reproductive care to prevent multiple gestations has led to a stronger emphasis on selecting embryos with the highest morphological quality. Although this evaluation has traditionally been performed by trained embryologists, the increasing use of time-lapse incubators has introduced a greater volume of data and subjectivity in decision-making. Artificial intelligence (AI)-based tools can support embryologists by offering objective, standardized embryo assessments.In Brazil, like other countries, where imported embryo selection technologies may not account for local demographic and ethnic profiles, an AI model - Morphological Artificial Intelligence Assistance (MAIA) - was developed through a collaboration between a university and a private fertility clinic in São Paulo. The model was trained using 1,015 embryo images and prospectively tested in a clinical setting on 200 single embryo transfers. In clinical testing, MAIA achieved an overall accuracy of 66.5%. In elective embryo transfers, where there were more than one embryo eligible for transfer, MAIA achieved 70.1% accuracy for predicting clinical pregnancy. Designed with a user-friendly interface tailored by embryologists, MAIA provides real-time embryo evaluations to support decision-making in routine care.

Scientific ReportsVol. 15(1)
Huntington University (US), Universidade Estadual Paulista (Unesp) (BR), Universidade Federal de São Paulo (BR)
Fundação de Amparo à Pesquisa do Estado de São Paulo
Openalex Percentile: Top 15%
Artificial Intelligence in Healthcare and Education
1.31
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.