1,812
Views
0
CrossRef citations to date
0
Altmetric
Original Article

A new model based on artificial intelligence to screening preterm birth

, ORCID Icon, , , , , , , , , , & show all
Article: 2241100 | Received 10 Feb 2022, Accepted 21 Jul 2023, Published online: 30 Jul 2023

References

  • Mercer BM, Goldenberg RL, Das A, et al. The preterm prediction study: a clinical risk assessment system. Am J Obstet Gynecol. 1996;174(6):1885–1895. doi: 10.1016/s0002-9378(96)70225-9.
  • Iams JD, Goldenberg RL, Meis PJ, et al. The length of the cervix and the risk of spontaneous premature delivery. N Engl J Med. 1996;334(9):567–572. doi: 10.1056/NEJM199602293340904.
  • To MS, Skentou CA, Royston P, et al. Prediction of patient-specific risk of early preterm delivery using maternal history and sonographic measurement of cervical length: a population-based prospective study. Ultrasound Obstet Gynecol. 2006;27(4):362–367. doi: 10.1002/uog.2773.
  • Beta J, Akolekar R, Ventura W, et al. Prediction of spontaneous preterm delivery from maternal factors, obstetric history and placental perfusion and function at 11–13 weeks. Prenat Diagn. 2011;31(1):75–83. doi: 10.1002/pd.2662.
  • Rolnik DL, Wright D, Poon LCY, et al. ASPRE trial: performance of screening for preterm pre-eclampsia. Ultrasound Obstet Gynecol. 2017;50(4):492–495. doi: 10.1002/uog.18816.
  • Chawanpaiboon S, Vogel JP, Moller AB, et al. Global, regional, and national estimates of levels of preterm birth in 2014: a systematic review and modelling analysis. Lancet Glob Health. 2019;7(1):e37–46–e46. doi: 10.1016/S2214-109X(18)30451-0.
  • Goldenberg RL, Culhane JF, Iams JD, et al. Epidemiology and causes of preterm birth. Lancet. [Internet]. 2008;371(9606):75–84. doi: 10.1016/S0140-6736(08)60074-4.
  • United Nations Inter-Agency Group for Child Mortality Estimation. Levels and Trends in Child Mortality - Report 2018. 2018;
  • Raghupathi W, Raghupathi V. Big data analytics in healthcare: promise and potential. Heal Inf Sci Syst. 2014;2(1):1–10.
  • Beyer MA, Laney D. The importance of “big data”: a definition. Gartner; 2012.
  • Ayodele TO. Types of machine learning algorithms. In: Zhang Y, editor. New Advances in Machine Learning. Rijeka: IntechOpen; 2010. p. 21–48.
  • Geron A. Hands-On machine learning with Scikit-Learn, keras & TensorFlow - Concepts, tools, and techniques to build intelligent systems. O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472; 2019. 1–510. p.
  • Wang Y, Wang D, Geng N, et al. Stacking-based ensemble learning of decision trees for interpretable prostate cancer detection. Appl Soft Comput J. [Internet]. 2019;77:188–204. doi: 10.1016/j.asoc.2019.01.015.
  • Hosny A, Parmar C, Quackenbush J, et al. Artificial intelligence in radiology. Nat Rev Cancer. 2018;18(8):500–510. doi: 10.1038/s41568-018-0016-5.
  • Arnold KC, Flint CJ. Cerclage for the management of cervical insufficiency. In: Arnold KC, Flint CJ, editors. Obstetrics Essentials. Cham: Springer; 2017. p. 173–177.
  • Pacagnella RC, Silva TV, Cecatti JG, et al. Pessary plus progesterone to prevent preterm birth in women with short cervixes: a randomized controlled trial. Obstet Gynecol. 2022;139(1):41–51. doi: 10.1097/AOG.0000000000004634.
  • Pacagnella RC, Mol B, Borovac-Pinheiro A, et al. A randomized controlled trial on the use of pessary plus progesterone to prevent preterm birth in women with short cervical length (P5 trial). BMC Pregnancy Childbirth. 2019;19(1):442. doi: 10.1186/s12884-019-2513-2.
  • Witkin SS, Moron AF, Ridenhour BJ, et al. Vaginal biomarkers that predict cervical length and dominant bacteria in the vaginal microbiomes of pregnant women downloaded from. MBio. [Internet]. 2019;10(1):e02242-19. doi: 10.1128/mBio.02242-19.
  • Hatanaka AR, Franca MS, Hamamoto TENK, et al. Antibiotic treatment for patients with amniotic fluid “sludge” to prevent spontaneous preterm birth: a historically controlled observational study. Acta Obstet Gynecol Scand. 2019;98(9):1157–1163. doi: 10.1111/aogs.13603.
  • Kagan KO, Sonek J. How to measure cervical length. Ultrasound Obstet Gynecol. 2015;45(3):358–362. doi: 10.1002/uog.14742.
  • Manssori J. What is vectorization in machine learning? [Internet]. June 2020. 2020. Available from: https://towardsdatascience.com/what-is-vectorization-in-machine-learning-6c7be3e4440a.
  • Austin PC, Tu JV. Automated variable selection methods for logistic regression produced unstable models for predicting acute myocardial infarction mortality. J Clin Epidemiol. 2004;57(11):1138–1146. doi: 10.1016/j.jclinepi.2004.04.003.
  • Mukaka MM. Statistics corner: a guide to appropriate use of correlation coefficient in medical research. Malawi Med J. 2012;24(3):69–71.
  • Kohavi R. A study of cross-validation and bootstrap for accuracy estimation and model selection. Int Jt Conf Artif Intell. 1995;2:1137–1145.
  • Pampel FC. Logisfic regression-A primer (quantitative applications in the social sciences). Thousand Oaks, CA: Sage Universal Paper; 2000.
  • Johnson RA, Wichern DW. Applied multivariate statistical analysis. 6th Ed. Upper Saddle River (NJ): Pearson Education; 2007.
  • Aha DW, Kibler D, Albert MK. Instance-based learning algorithms. Mach Learn. 1991;6(1):37–66. doi: 10.1007/BF00153759.
  • Santos RAF, De Barros RSM. Comparing FBTSeg and NNTree implementations with established ensemble methods. Proc - Int Conf Tools with Artif Intell ICTAI. 2012;1(11):898–903.
  • Conover W. Practical nonparametric statistic. 3rd ed. New York (NY): John Wiley & Sons; 1999.
  • Dezeroski S, B Z. Is combining classifiers with stacking better than selecting the best one? Mach Learn. 2004;40(2):50–62.
  • Van Rossum GD. Python reference manual. Amsterdam: Centrum voor Wiskunde en Informatica; 1995.
  • Hammad KAI, Mohammed AIF, Zain JM, et al. Big data analysis and storage. Proc 2015 Int Conf Oper Excell Serv Eng. 2015;(9):648–659.
  • Ricciardi W, Pita Barros P, Bourek A, et al. How to govern the digital transformation of health services. Eur J Public Health. 2019;29(Supplement_3):7–12. doi: 10.1093/eurpub/ckz165.
  • Celik E, To M, Gajewska K, et al. Cervical length and obstetric history predict spontaneous preterm birth: development and validation of a model to provide individualized risk assessment. Ultrasound Obstet Gynecol. 2008;31(5):549–554. doi: 10.1002/uog.5333.
  • Pernía-Espinoza A, Fernandez-Ceniceros J, Antonanzas J, et al. Stacking ensemble with parsimonious base models to improve generalization capability in the characterization of steel bolted components. Appl Soft Comput J. [Internet]. 2018;70:737–750. doi: 10.1016/j.asoc.2018.06.005.
  • Martin JA, Hamilton BE, Sutton PD, et al. Births: final data for 2005. Natl Vital Stat Rep. 2007;56(6):1–103.
  • Russell RB, Green NS, Steiner CA, et al. Cost of hospitalization for preterm and low birth weight infants in the United States. Pediatrics. 2007;120(1):e1–e9. doi: 10.1542/peds.2006-2386.
  • He J, Baxter SL, Xu J, et al. The practical implementation of artificial intelligence technologies in medicine. Nature. 2019;25(1):30–36.
  • Nicolaides KH. Nuchal translucency and other first-trimester sonographic markers of chromosomal abnormalities. Am J Obstet Gynecol. 2004;191(1):45–67. doi: 10.1016/j.ajog.2004.03.090.
  • Moher D, Wells GA, Dulberg CS. Statistical power, sample size, and their reporting in randomized controlled trials. JAMA. 1994;272(2):122–124. doi: 10.1001/jama.1994.03520020048013.
  • Wilson JMG, Jungner G. Principes and practice of screening for disease. J R Coll Gen Pract. 1968;16(4):318.
  • Pergialiotis V, Bellos I, Antsaklis A, et al. Presence of amniotic fluid sludge and pregnancy outcomes: a systematic review. Acta Obstet Gynecol Scand. 2020;99(11):1434–1443. doi: 10.1111/aogs.13893.
  • Romero R, Conde-Agudelo A, Da Fonseca E, et al. Vaginal progesterone for preventing preterm birth and adverse perinatal outcomes in sigleton gestations with a short cervix: meta-analysis of individual patient data. Am J Obstet Gynecol. 2018;218(2):161–180. doi: 10.1016/j.ajog.2017.11.576.
  • Alfirevic Z, Owen J, Carreras Moratonas E, et al. Vaginal progesterone, cerclage or cervical pessary for preventing preterm birth in asymptomatic singleton pregnant women with a history of preterm birth and a sonographic short cervix. Ultrasound Obstet Gynecol. 2013;41(2):146–151. doi: 10.1002/uog.12300.