20.500.12556/RUL-164454 An open dataset with electrohysterogram records of pregnancies ending in induced and cesarean section delivery The existing non-invasive automated preterm birth prediction methods rely on the use of uterine electrohysterogram (EHG) records coming from spontaneous preterm and term deliveries, and are indifferent to term induced and cesarean section deliveries. In order to enhance current publicly available pool of term EHG records, we developed a new EHG dataset, Induced Cesarean EHG DataSet (ICEHG DS), containing 126 30-minute EHG records, recorded early (23rd week), and/or later (31st week) during pregnancy, of those pregnancies that were expected to end in spontaneous term delivery, but ended in induced or cesarean section delivery. The records were collected at the University Medical Center Ljubljana, Ljubljana, Slovenia. The dataset includes 38 and 43, early and later, induced; 11 and 8, early and later, cesarean; and 13 and 13, early and later, induced and cesarean EHG records. This dataset enables better understanding of the underlying physiological mechanisms involved during pregnancies ending in induced and cesarean deliveries, and provides a robust and more realistic assessment of the performance of automated preterm birth prediction methods. electrohysterogram electrohysterogram records term birth prediction induced birth cesarean section delivery preterm birth prediction electromyography EMG learning algorithms elektrohisterogram posnetki elektrohisterograma napoved terminskega poroda inducirani porod carski porod napoved prezgodnjega poroda true false true Angleški jezik Slovenski jezik Članek v reviji 2024-10-25 12:38:40 2024-10-25 12:38:42 2024-11-22 14:54:24 0000-00-00 00:00:00 2023 0 0 12 str. art. 669 Vol. 10 2023 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004:618.39 2052-4463 10.1038/s41597-023-02581-6 166694659 s41597-023-02581-6.pdf s41597-023-02581-6.pdf 1 A6A7B7A964C56F7FB71BC7C6509F7F2B d10764bbb52378fdb641071675fa1b30ff2265cf5072128f7bbc0ff5db7716d8 3034b40e-92bd-11ef-b232-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=194866 https://www.nature.com/articles/s41597-023-02581-6 1 010850d2-92bd-11ef-b232-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=194865 Fakulteta za računalništvo in informatiko 0 0 0