ArticleTranslational oncology2021
Novel artificial intelligence machine learning approaches to precisely predict survival and site-specific recurrence in cervical cancer: A multi-institutional study.
Article in Translational oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05771532 (Evaluation of a Gender-sensitive Sexual Health Education Program for Women With Gynecologic Cancer), which is not on this map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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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.
Evaluation of a Gender-sensitive Sexual Health Education Program for Women With Gynecologic Cancer: A Prospective and Randomized Controlled Evaluation of Sexual Health Education Program of Cervical Cancer Women
Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Cervical cancer survival prediction by machine learning algorithms: a systematic review.BMC cancer · 2023Pooled it
- Machine Learning-driven Prediction of Cervical Cancer Cell Viability After Treatment With Thymoquinone, Curcumin, and 5-Fluorouracil.Applied biochemistry and biotechnology · 2026Article
- Innovations in biomarker stratification for precision oncology.Clinical and experimental medicine · 2026Review
- Survival Period Prediction in Cervical Cancer Patients Using the Selective Stacking Technique.Healthcare informatics research · 2026Article
- Integrative Long Non-Coding RNA Analysis and Recurrence Prediction in Cervical Cancer Using a Recurrent Neural Network.Diagnostics (Basel, Switzerland) · 2025Article
- Machine Learning-Based Prognostic Modelling Using MRI Radiomic Data in Cervical Cancer Treated with Definitive Chemoradiotherapy and Brachytherapy.Current oncology (Toronto, Ont.) · 2025Article
- Article
- Recent advances in applications of machine learning in cervical cancer research: a focus on prediction models.Obstetrics & gynecology science · 2025Article
- Integrating Clinical and Transcriptomic Profiles Associated with Vitamin D to Enhance Disease-Free Survival in Cervical Cancer Recurrence Using the CatBoost Algorithm.Diagnostics (Basel, Switzerland) · 2025Article
- ConvXGB: A novel deep learning model to predict recurrence risk of early-stage cervical cancer following surgery using multiparametric MRI images.Translational oncology · 2025Article
- A Review on the Applications of Artificial Intelligence for Diagnosing and Treating Cervical Cancer.International journal of women's health · 2025Review
- Bidirectional recurrent neural network approach for predicting cervical cancer recurrence and survival.Scientific reports · 2024Article
- Prognostic Factors for Cervical Cancer in Asian Populations: A Scoping Review of Research From 2013 to 2023.Cureus · 2024Article
- Integrating cat boost algorithm with triangulating feature importance to predict survival outcome in recurrent cervical cancer.Scientific reports · 2024Article
- Artificial Intelligence Needs Data: Challenges Accessing Italian Databases to Train AI.Asian bioethics review · 2024Article
- A novel higher performance nomogram based on explainable machine learning for predicting mortality risk in stroke patients within 30 days based on clinical features on the first day ICU admission.BMC medical informatics and decision making · 2024Article
- Pre-treatment T2-weighted magnetic resonance radiomics for prediction of loco-regional recurrence after image-guided adaptive brachytherapy for locally advanced cervical cancer.Journal of contemporary brachytherapy · 2024Article
- A Deep Learning-Based Approach for Cervical Cancer Classification Using 3D CNN and Vision Transformer.Journal of imaging informatics in medicine · 2024Article
- Prediction of Cervical Cancer Patients' Survival Period with Machine Learning Techniques.Healthcare informatics research · 2024Article
- Hybrid Model for Detection of Cervical Cancer Using Causal Analysis and Machine Learning Techniques.Computational and mathematical methods in medicine · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMachine learning (ML) has been gradually integrated into oncologic research but seldom applied to predict cervical cancer (CC), and no model has been reported to predict survival and site-specific recurrence simultaneously. Thus, we aimed to develop ML models to predict survival and site-specific recurrence in CC and to guide individual surveillance.
methodsWe retrospectively collected data on CC patients from 2006 to 2017 in four hospitals. The survival or recurrence predictive value of the variables was analyzed using multivariate Cox, principal component, and K-means clustering analyses. The predictive performances of eight ML models were compared with logistic or Cox models. A novel web-based predictive calculator was developed based on the ML algorithms.
resultsThis study included 5112 women for analysis (268 deaths, 343 recurrences): (1) For site-specific recurrence, larger tumor size was associated with local recurrence, while positive lymph nodes were associated with distant recurrence. (2) The ML models exhibited better prognostic predictive performance than traditional models. (3) The ML models were superior to traditional models when multiple variables were used. (4) A novel predictive web-based calculator was developed and externally validated to predict survival and site-specific recurrence.
conclusionML models might be a better analytic approach in CC prognostic prediction than traditional models as they can predict survival and site-specific recurrence simultaneously, especially when using multiple variables. Moreover, our novel web-based calculator may provide clinicians with useful information and help them make individual postoperative follow-up plans and further treatment strategies.
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