ArticleEClinicalMedicine2024
Risk of intraoperative hemorrhage during cesarean scar ectopic pregnancy surgery: development and validation of an interpretable machine learning prediction model.
Article in EClinicalMedicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine Learning in Assessing Intraoperative Blood Loss: A Systematic Review and Meta-Analysis.International nursing review · 2026Pooled it
- Risk prediction of non-small cell lung cancer in patients with pulmonary nodules: a single-center cohort study based on six machine learning algorithms.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- An interpretable machine learning model for diabetic foot risk classification in patients with diabetes.Scientific reports · 2026Article
- Machine Learning for Intraoperative Bleeding Prediction in Patients Undergoing Surgery: Scoping Review.JMIR medical informatics · 2026Article
- An explainable predictive machine learning model of oxaliplatin induced peripheral neuropathy based on clinical data: a retrospective single center.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026Article
- An explainable ensemble learning-based auxiliary diagnosis system for cerebral small vessel disease.Scientific reports · 2026Article
- Surgical bleeding prediction using transformer: an application to laparoscopic cholecystectomy.International journal of computer assisted radiology and surgery · 2026Article
- Interpretable multimodal PET/CT-EHR fusion via mixture-of-experts for prognostic stratification in mantle cell lymphoma: a multicenter study.BMC medicine · 2026Article
- Artificial intelligence-enabled clinical decision support systems in preadmission testing: a scoping review of risk prediction, triage, and perioperative workflows (2020-2025).Journal of clinical monitoring and computing · 2026Article
- From a Multi-Omics Signature to a Therapeutic Candidate: Computational Prediction and Experimental Validation in Liver Fibrosis.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Foundation Model-Enabled Multimodal Deep Learning for Prognostic Prediction in Colorectal Cancer with Incomplete Modalities: A Multi-Institutional Retrospective Study.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Development and validation of interpretable multimodal clinical-radiomics models for predicting epileptogenic foci and surgical outcomes in tuberous sclerosis complex: A multicenter study.PLOS digital health · 2026Article
- Machine learning analysis of pregnancy-related factors and stillbirth: a retrospective cohort study of 65,000 pregnant women in Shuyang, Suqian, Jiangsu, China, 2019-2024.BMC pregnancy and childbirth · 2026Article
- Data-driven classification of playing styles and match outcome prediction in UEFA Champions League teams.Biology of sport · 2026Article
- Artificial Intelligence in Patient Blood Management: A Systematic Review of Predictive, Diagnostic, and Decision Support Applications.Journal of clinical medicine · 2025Review
- Machine learning prediction of overall survival in patients with cT1b renal cell carcinoma after surgical resection using the SEER database.Scientific reports · 2025Article
- Development and Validation of An Interpretable Machine Learning-Based Prediction Model of Postpartum Hemorrhage in Placenta Previa Following Cesarean Section: A Multicenter Study.Reproductive sciences (Thousand Oaks, Calif.) · 2025Article
- Machine Learning-Based Prediction of Post-Operative Systemic Inflammatory Response Syndrome Following Pediatric Percutaneous Nephrolithotripsy.Journal of inflammation research · 2025Article
- Uterine arteries embolization for cesarean scar pregnancy with uterine arteriovenous fistula.SAGE open medical case reports · 2025Article
- Prediction Models of Microinvasive Cervical Cancer in High-Grade Squamous Intraepithelial Lesion Treatment by Loop Electrosurgical Excision Procedure.Risk management and healthcare policy · 2025Article
Corrections and comments
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Current models for predicting intraoperative hemorrhage in cesarean scar ectopic pregnancy (CSEP) are constrained by known risk factors and conventional statistical methods. Our objective is to develop an interpretable prediction model using machine learning (ML) techniques to assess the risk of intraoperative hemorrhage during CSEP in women, followed by external validation and clinical application. Methods: This multicenter retrospective study utilized electronic medical record (EMR) data from four tertiary medical institutions. The model was developed using data from 1680 patients with CSEP diagnosed and treated at Qilu Hospital of Shandong University, Chongqing Health Center for Women and Children, and Dezhou Maternal and Child Health Care Hospital between January 1, 2008, and December 31, 2023. External validation data were obtained from Liao Cheng Dong Chang Fu District Maternal and Child Health Care Hospital between January 1, 2021, and December 31, 2023. Random forest (RF), Lasso, Boruta, and Extreme Gradient Boosting (XGBoost) were employed to identify the most influential variables in the model development data set; the best variables were selected based on reaching the λ Findings: Setting λ Interpretation: The developed prediction model, deployed in the network application, is capable of forecasting the risk of intraoperative hemorrhage during CSEP. This tool can facilitate targeted preoperative assessment and clinical decision-making for clinicians. Prospective data should be utilized in future studies to further validate the extended applicability of the model. Funding: Natural Science Foundation of Shandong Province; Qilu Hospital of Shandong University.
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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 Socratic graph.