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Interpretable Machine Learning for Personalized Prediction of Live Birth in Women with Diminished Ovarian Reserve: A Large-Scale Retrospective Cohort Study

Interpretable Machine Learning for Personalized Prediction of Live Birth in Women with Diminished Ovarian Reserve: A Large-Scale Retrospective Cohort Study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600124331
Enrollment
Unknown
Registered
2026-05-11
Start date
2026-05-11
Completion date
Unknown
Last updated
2026-05-18

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Diminished Ovarian Reserve, DOR

Interventions

Live birth group:None

Sponsors

Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University
Lead Sponsor

Eligibility

Sex/Gender
Female
Age
20 Years to 50 Years

Inclusion criteria

Inclusion criteria: Patients with DOR who meet the Bologna Criteria or the POSEIDON standards (Group 3 & 4): 1.Age: 20 <= age <= 50 years; 2.Diminished ovarian reserve: AFC < 5-7 follicles and/or AMH < 1.1 ng/mL; 3.History of poor ovarian response: Number of oocytes retrieved with a conventional stimulation protocol = 3; 4.Completion of at least one full IVF/ICSI oocyte retrieval cycle, with clear documentation of pregnancy outcome follow-up;

Exclusion criteria

Exclusion criteria: 1.Concurrent severe organic uterine pathologies significantly affecting implantation (e.g., severe intrauterine adhesions, untreated submucosal fibroids, congenital uterine malformations, etc.); 2.Either partner having a confirmed chromosomal karyotype abnormality; 3.Cases where missing rates of core clinical data (e.g., key hormone levels, ovulation induction parameters, pregnancy outcomes) exceeded 20% and could not be repaired through imputation;

Design outcomes

Primary

MeasureTime frame
Live birth rate;Discriminative ability of the predictive model;

Secondary

MeasureTime frame
Specificity;Sensitivity;Net Benefit;Feature Importance Ranking and Variable Interactions: Interaction Effects and Nonlinear Associations.;calibration;

Countries

China

Contacts

Public ContactShi Libing

Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University

shilibing1215@zju.edu.cn+86 571 86002222

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: May 22, 2026