Citation: Kuzu, A.; Santur, Y. Early Diagnosis and Classification of Fetal Health Status from a Fetal Cardiotocography Dataset Using Ensemble Learning. Diagnostics 2023, 13, 2471. https://doi.org/10.3390/ diagnostics13152471 Academic Editor: Ayman El-Baz Received: 9 July 2023 Revised: 21 July 2023 Accepted: 22 July 2023 Published: 25 July 2023 Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). diagnostics Article Early Diagnosis and Classification of Fetal Health Status from a Fetal Cardiotocography Dataset Using Ensemble Learning Adem Kuzu 1 and Yunus Santur 2, * 1 Department of Software Engineering, Firat University, Elazig 23119, Turkey; ademkuzu@gmail.com 2 Department of Artificial Intelligence and Data Engineering, Firat University, Elazig 23119, Turkey * Correspondence: ysantur@firat.edu.tr Abstract: (1) Background: According to the World Health Organization (WHO), 6.3 million intrauter- ine fetal deaths occur every year. The most common method of diagnosing perinatal death and taking early precautions for maternal and fetal health is a nonstress test (NST). Data on the fetal heart rate and uterus contractions from an NST device are interpreted based on a trace printer’s output, allowing for a diagnosis of fetal health to be made by an expert. (2) Methods: in this study, a predictive method based on ensemble learning is proposed for the classification of fetal health (normal, suspicious, pathology) using a cardiotocography dataset of fetal movements and fetal heart rate acceleration from NST tests. (3) Results: the proposed predictor achieved an accuracy level above 99.5% on the test dataset. (4) Conclusions: from the experimental results, it was observed that a fetal health diagnosis can be made during NST using machine learning. Keywords: ensemble learning; fetal health; FHR; NST 1. Introduction Fetal deaths occurring between the 22nd week of pregnancy and the first 7 days after birth are known as perinatal mortality [1]. The World Health Organization (WHO) has reported that 6.3 million perinatal deaths occur every year. In this report, perinatal cases are scaled to a value per 1000 births, and the development rates of countries are considered to be a critical factor affecting this rate. While this value is lower than 10 in developed countries, it is higher in less developed ones and exceeds 30 in underdeveloped countries [2]. Perinatal cases may result in maternal poisoning/death as well as death for the fetus/infant. The most effective method of early diagnosis is to perform a periodic nonstress test (NST). From the 32nd week of pregnancy, an NST procedure is required every week. The NST device is typically connected to a pregnant woman for 20 min, with two separate probes recording data on fetal heart rate (FHR) and uterine contractions (UCs) [3,4]. The NST device has a memory unit and generates a trace by obtaining FHR and UC data with respect to a basal average of 10 s, as shown in Figure 1. Figure 1. Example of an NST trace. Diagnostics 2023, 13, 2471. https://doi.org/10.3390/diagnostics13152471 https://www.mdpi.com/journal/diagnostics