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Comparison of fetal heart rate baseline estimation by the cardiotocograph network and clinicians: a multidatabase retrospective assessment study

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机构： [1]Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Information Technology, Jinan University, Guangzhou, China. [2]College of Information Science and Technology, Jinan University, Guangzhou, China. [3]Auckland Bioengnieering Institute, The University of Auckland, Auckland, New Zeanland. [4]Department of Obstetrics and Gynecology, Guangzhou Women and Children's Medical Center, Preterm Birth Prevention and Treatment Research Unit, Guangzhou Medical University, Guangzhou, China. [5]Department of Obstetrics, NanFang Hospital of Southen Medical University, Guangzhou, China. [6]Department of Obstetrics, Shenzhen People's Hospital, Shenzhen, China.

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关键词： artificial intelligence deep learning fetal heart rate baseline computer analysis

摘要：

This study aims to compare the fetal heart rate (FHR) baseline predicted by the cardiotocograph network (CTGNet) with that estimated by clinicians.A total of 1,267 FHR recordings acquired with different electrical fetal monitors (EFM) were collected from five datasets: 84 FHR recordings acquired with F15 EFM (Edan, Shenzhen, China) from the Guangzhou Women and Children's Medical Center, 331 FHR recordings acquired with SRF618B5 EFM (Sanrui, Guangzhou, China), 234 FHR recordings acquired with F3 EFM (Lian-Med, Guangzhou, China) from the NanFang Hospital of Southen Medical University, 552 cardiotocographys (CTG) recorded using STAN S21 and S31 (Neoventa Medical, Mölndal, Sweden) and Avalon FM40 and FM50 (Philips Healthcare, Amsterdam, The Netherlands) from the University Hospital in Brno, Czech Republic, and 66 FHR recordings acquired using Avalon FM50 fetal monitor (Philips Healthcare, Amsterdam, The Netherlands) at St Vincent de Paul Hospital (Lille, France). Each FHR baseline was estimated by clinicians and CTGNet, respectively. And agreement between CTGNet and clinicians was evaluated using the kappa statistics, intra-class correlation coefficient, and the limits of agreement.The number of differences <3 beats per minute (bpm), 3-5 bpm, 5-10 bpm and ≥10 bpm, is 64.88%, 15.94%, 14.44% and 4.74%, respectively. Kappa statistics and intra-class correlation coefficient are 0.873 and 0.969, respectively. Limits of agreement are -6.81 and 7.48 (mean difference: 0.36 and standard deviation: 3.64).An excellent agreement was found between CTGNet and clinicians in the baseline estimation from FHR recordings with different signal loss rates.© 2023 Bai, Pan, Lu, Zhong, Wang, Zheng and Guo.

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出版当年[2022]版：

大类 | 3 区医学

小类 | 3 区心脏和心血管系统

最新[2025]版：

大类 | 3 区医学

小类 | 3 区心脏和心血管系统

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出版当年[2021]版：

Q2 CARDIAC & CARDIOVASCULAR SYSTEMS

最新[2023]版：

Q2 CARDIAC & CARDIOVASCULAR SYSTEMS

影响因子： 2.8 最新[2023版] 3.1 最新五年平均 5.848 出版当年[2021版] 6.221 出版当年五年平均 6.05 出版前一年[2020版] 3.6 出版后一年[2022版]

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第一作者机构： [1]Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Information Technology, Jinan University, Guangzhou, China. [2]College of Information Science and Technology, Jinan University, Guangzhou, China. [3]Auckland Bioengnieering Institute, The University of Auckland, Auckland, New Zeanland.

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Comparison of fetal heart rate baseline estimation by the cardiotocograph network and clinicians: a multidatabase retrospective assessment study

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