ArticleBMJ open2025
Blastocyst selection through an interpretable artificial intelligence method versus traditional morphology grading: study protocol for a randomised controlled trial.
Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe quality of the blastocyst (day 5/6 embryo) selected for transfer is critical for the success of in vitro fertilisation (IVF) treatment. Embryologists perform blastocyst evaluation by observing the morphology of each blastocyst. Human assessment is subjective and inconsistent in predicting which blastocyst can result in a successful pregnancy or birth. Several artificial intelligence (AI) methods have been proposed to predict IVF outcomes from blastocyst images. However, the reasoning processes of these AI methods are uninterpretable, causing epistemic and ethical concerns that prevent their implementation in clinical practice. To address this issue, the authors developed a novel interpretable AI method for blastocyst selection. The method is clinically applicable because it is transparent to embryologists and allows them to understand its reasoning processes. This randomised controlled trial (RCT) aims to test the effectiveness of this blastocyst selection method with the aim of improving IVF outcomes. METHODS AND ANALYSIS: In this single-centre, single-blind RCT, we will enrol 1100 women aged 20-35 years undergoing their first cycle of IVF, with or without intracytoplasmic sperm injection. The study will be conducted at Nanjing Drum Tower Hospital, a public class A tertiary hospital in China. On the fifth day of embryo culture, participants with two or more usable blastocysts will be randomised in a 1:1 ratio to either the conventional morphology group or the AI group. The primary outcome is ongoing pregnancy, defined as a viable intrauterine pregnancy of 12 weeks gestation or more. ETHICS AND DISSEMINATION: The research ethics committee of the Nanjing Drum Tower Hospital approved this study (approval number: 2023-259-02). All participants will provide written informed consent prior to enrolment. The findings will be presented at international conferences and published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: ChiCTR2300076851.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.