New advances in prediction and surveillance of preeclampsia: role of machine learning approaches and remote monitoring.
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| Title: | New advances in prediction and surveillance of preeclampsia: role of machine learning approaches and remote monitoring. |
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| Authors: | Hackelöer M; Department of Obstetrics, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt- Universität Zu Berlin, Charitéplatz 1, 10117, Berlin, Germany., Schmidt L; Department of Obstetrics, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt- Universität Zu Berlin, Charitéplatz 1, 10117, Berlin, Germany., Verlohren S; Department of Obstetrics, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt- Universität Zu Berlin, Charitéplatz 1, 10117, Berlin, Germany. stefan.verlohren@charite.de. |
| Source: | Archives of gynecology and obstetrics [Arch Gynecol Obstet] 2023 Dec; Vol. 308 (6), pp. 1663-1677. Date of Electronic Publication: 2022 Dec 25. |
| Publication Type: | Journal Article; Review |
| Journal Info: | Publisher: Springer Verlag Country of Publication: Germany NLM ID: 8710213 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-0711 (Electronic) Linking ISSN: 09320067 NLM ISO Abbreviation: Arch Gynecol Obstet Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1432-0711 |
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| DOI: | 10.1007/s00404-022-06864-y |
