A deep learning mixed-data type approach for the classification of FHR signals

Review Anesthesiology

Power spectrum and spectrogram of EEG analysis during general anesthesia: Python-based computer programming analysis

Teiji Sawa et al.

Summary: This paper reviews the techniques for analyzing the relationship between the depth of anesthesia and EEG frequency during general anesthesia by constructing an effective spectrum and spectrogram. Various computer programming methods, such as the periodogram and multitaper method, are used to analyze EEG frequency and help understand anesthesia depth.

JOURNAL OF CLINICAL MONITORING AND COMPUTING (2022)

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Review Obstetrics & Gynecology

Artificial intelligence in obstetrics

Ki Hoon Ahn et al.

Summary: This study reviews recent advances in the application of artificial intelligence for early diagnosis of various maternal-fetal conditions and highlights the successful use of different machine learning methods for data capture. However, ethical issues need to be taken into consideration with the increasing use of artificial intelligence.

OBSTETRICS & GYNECOLOGY SCIENCE (2022)

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Article Health Care Sciences & Services

Doppler Ultrasound Imaging Combined with Fetal Heart Detection in Predicting Fetal Distress in Pregnancy-Induced Hypertension under the Guidance of Artificial Intelligence Algorithm

Su Liu et al.

Summary: This study aimed to improve the feasibility and economic benefits of using intelligent medical system Doppler ultrasound (DUS) imaging technology combined with fetal heart detection to predict fetal distress in pregnancy-induced hypertension (PIH). The results showed that the combined DUS testing and fetal heart monitoring had a significantly higher diagnostic accuracy for fetal distress compared to simple fetal heart monitoring, reducing the risk of deterioration in patient condition. Furthermore, the values detected by DUS diagnosis in the umbilical artery and middle cerebral artery effectively reflect the current status of the fetus and have important reference value for the development of intelligent medical equipment.

JOURNAL OF HEALTHCARE ENGINEERING (2021)

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Review Medicine, General & Internal

Non-linear Methods Predominant in Fetal Heart Rate Analysis: A Systematic Review

Maria Ribeiro et al.

Summary: The analysis of fetal heart rate variability using non-linear methods such as chaos, fractality, and complexity concepts has shown promise in assessing various prenatal conditions, offering insight into fetal well-being. However, critical concerns currently prevent their clinical application, and future studies should focus on combining linear and non-linear indices for more accurate analysis.

FRONTIERS IN MEDICINE (2021)

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Article Computer Science, Interdisciplinary Applications