Modeling Multiple Adverse Pregnancy Outcomes: Learning from Diverse Data Sources

Author:

Mathur Saurabh,Gadekar Veerendra P.,Ramola Rashika,Wang Peixin,Thiruvengadam Ramachandran,Haas David M.,Bhatnagar Shinjini,Wadhwa Nitya,Study Group Garbhini,Radivojac Predrag,Sinha Himanshu,Kersting Kristian,Natarajan Sriraam

Publisher

Springer Nature Switzerland

Reference26 articles.

1. Bhatnagar, S., Majumder, P.P., Salunke, D.M.: A pregnancy cohort to study multidimensional correlates of preterm birth in India: study design, implementation, and baseline characteristics of the participants. Am. J. Epidemiol. 188(4), 621–631 (2019)

2. Bohiltea, R.E., et al.: Impact of obesity on the prognosis of hypertensive disorders in pregnancy. Exp. Ther. Med. 20(3), 2423–2428 (2020)

3. Boutilier, C., Friedman, N., Goldszmidt, M., Koller, D.: Context-specific independence in bayesian networks. In: Proceedings of the Twelfth International Conference on Uncertainty in Artificial Intelligence, pp. 115–123 (1996)

4. Breiman, L., Friedman, J.H., Olshen, R.A., Stone, C.J.: Classification and Regression Trees. Wadsworth (1984)

5. Brown, T., et al.: Language models are few-shot learners. Adv. Neural. Inf. Process. Syst. 33, 1877–1901 (2020)

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