Predicting pregnancy using large-scale data from a women's health tracking mobile application-Reference-Cited by-同舟云学术

Predicting pregnancy using large-scale data from a women's health tracking mobile application

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:The World Wide Web Conference on - WWW '19
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Author:

Liu Bo¹,Shi Shuyang¹,Wu Yongshang¹,Thomas Daniel²,Symul Laura³,Pierson Emma¹,Leskovec Jure⁴

Affiliation:

1. Dept. of Computer Science, Stanford

2. Clue by BioWink GmbH, Berlin

3. Dept. of General Surgery and Dept. of Statistics, Stanford

4. Dept. of Computer Science, Stanford and Chan-Zuckerberg Biohub

Publisher

ACM Press

Reference52 articles.

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2. Alexandra Alvergne, Marija Vlajic Wheeler, and Vedrana Högqvist Tabor. 2018. Do sexually transmitted infections exacerbate negative premenstrual symptoms? Insights from digital health. Evolution, Medicine, and Public Health(2018).

3. John C Barrett and John Marshall. 1969. The risk of conception on different days of the menstrual cycle. Population Studies 23, 3 (1969), 455-461.

4. Inci M Baytas, Cao Xiao, Xi Zhang, Fei Wang, Anil K Jain, and Jiayu Zhou. 2017. Patient subtyping via time-aware LSTM networks. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 65-74.

5. Jamie L Bigelow, David B Dunson, Joseph B Stanford, Rene´ Ecochard, Christian Gnoth, and Bernardo Colombo. 2004. Mucus observations in the fertile window: a better predictor of conception than timing of intercourse. Human Reproduction 19, 4 (2004), 889-892.

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