Sample Tool

Maternal Characteristics

Pregnancy Details

Bishop Score Components

Bishop Score: 0 / 13

Optional: Ultrasound Cervical Assessment

📚 Evidence Base: Publications Informing This Model ▸

Feature selection, weighting, and clinical logic are based on peer-reviewed studies (click to expand)

Machine Learning Prediction Models for Induction Outcomes
  1. Ferreira I, Simões J, Pereira B, et al. Predicting vaginal delivery after labor induction using machine learning: development of a multivariable prediction model. Acta Obstet Gynecol Scand. 2025;104(3):489-99. doi: 10.1111/aogs.14953
  2. Ferreira I, Simões J, Pereira B, et al. Ensemble learning for fetal ultrasound and maternal-fetal data to predict mode of delivery after labor induction. Sci Rep. 2024;14:15275. doi: 10.1038/s41598-024-65394-6
  3. Krsman A, Grujić Z, Čapko D, et al. Ultrasound assessment of cervical status compared to the Bishop score: predicting the success of labor induction using a machine learning-based model. Eur Rev Med Pharmacol Sci. 2023;27(13):6332-42. doi: 10.26355/eurrev_202307_32993
  4. Zhang Y, Liu X, Wang Y, et al. Establishment of a model for predicting the outcome of induced labor in full-term pregnancy based on machine learning algorithm. Sci Rep. 2022;12:19154. doi: 10.1038/s41598-022-21954-2
  5. Abdelgadir Elhabeeb SM, Ali SHM, et al. Enhancing obstetric decision-making with AI: a systematic review of AI models for predicting mode of delivery. Cureus. 2025;17(5):e83655. doi: 10.7759/cureus.83655
Induction of Labor: Methods, Pharmacology & Protocols (AJOG)
  1. Sanchez-Ramos L, Levine LD, Sciscione AC, et al. Methods for the induction of labor: efficacy and safety. Am J Obstet Gynecol. 2024;230(3S):S669-S695. doi: 10.1016/j.ajog.2023.01.029
  2. Hermesch AC, Engstrom JL, Grobman WA. Oxytocin: physiology, pharmacology, and clinical application for labor management. Am J Obstet Gynecol. 2024;230(3S):S625-S642. doi: 10.1016/j.ajog.2023.07.031
  3. Grasch JL, Costantine MM, Cahill AG, et al. High- vs low-dose oxytocin protocols for labor induction: a systematic review and meta-analysis. Am J Obstet Gynecol MFM. 2025;7(7):101691. doi: 10.1016/j.ajogmf.2025.101691
  4. Azria E, Haaser T, Schmitz T, et al. The ethics of induction of labor at 39 weeks in low-risk nulliparas in research and clinical practice. Am J Obstet Gynecol. 2024;230(3S):S775-S782. doi: 10.1016/j.ajog.2023.07.037
Bishop Score Validation & Limitations
  1. Bishop EH. Pelvic scoring for elective induction. Obstet Gynecol. 1964;24:266-8.
  2. Role of the Bishop score in predicting successful induction of vaginal delivery: a systematic review of current evidence. Cureus. 2025. doi: 10.7759/cureus.384440
Stillbirth & Adverse Outcome Prediction
  1. Malacova E, Tippaya S, Bailey HD, et al. Stillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980-2015. Sci Rep. 2020;10:5354. doi: 10.1038/s41598-020-62210-9
  2. Magee LA, Engelbrecht E, von Dadelszen P, et al. Machine learning-enabled maternal risk assessment for women with pre-eclampsia (the PIERS-ML model): a modelling study. Lancet Digit Health. 2024;6(4):e238-50. doi: 10.1016/S2589-7500(23)00267-4
Algorithmic Bias & Equity
  1. Obermeyer Z, Powers B, Vogeli C, Mullainathan S. Dissecting racial bias in an algorithm used to manage the health of populations. Science. 2019;366(6464):447-53. doi: 10.1126/science.aax2342
Cervical Ripening & Mechanical Methods
  1. Jones NR, Moffett A, Sharp AN, et al. Balloon catheters versus vaginal prostaglandins for cervical ripening and labour induction (CPI collaborative): systematic review and individual participant data meta-analysis. BMJ. 2023;383:e076370. doi: 10.1136/bmj-2023-076370
  2. Hofmeyr GJ, Gülmezoglu AM, Pileggi C. Vaginal misoprostol for cervical ripening and induction of labour. Cochrane Database Syst Rev. 2010;(10):CD000941. doi: 10.1002/14651858.CD000941.pub2
AI in Obstetric Decision-Making
  1. Grünebaum A, Dudenhausen J, Chervenak FA. Enhancing patient understanding in obstetrics: the role of generative AI in simplifying informed consent for labor induction with oxytocin. J Perinat Med. 2025;53(6):688-95. doi: 10.1515/jpm-2024-0428
  2. Parvinian B, Scully C, Wiyor H, Kumar A, Weininger S. Regulatory considerations for physiological closed-loop controlled medical devices used for automated critical care. Anesth Analg. 2018;126(6):1916-24. doi: 10.1213/ANE.0000000000002531
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Enter patient data and click Generate AI Induction Assessment to see individualized predictions.

This is a demonstration prototype.
Not for clinical use.

Analyzing patient profile against simulated induction database...