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Comprehensive miscarriage dataset for an early miscarriage prediction
We present risk factors for predicting miscarriage. Our data is created through an android mobile application that collects automatically real-time data about the pregnant woman. This process is done every 60 s while the mobile application is on active mode. We distinguish two types of data: data fr...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5992995/ https://www.ncbi.nlm.nih.gov/pubmed/29892640 http://dx.doi.org/10.1016/j.dib.2018.05.012 |
| Sumario: | We present risk factors for predicting miscarriage. Our data is created through an android mobile application that collects automatically real-time data about the pregnant woman. This process is done every 60 s while the mobile application is on active mode. We distinguish two types of data: data from mobile phone and data from healthcare sensors. Data generated is real and concerns real pregnant women to test and validate the proposed system and assess its performance and effectiveness. |
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