Abstract
Preeclampsia detection research has started exploring some methods to diagnose and predict preeclampsia. Machine learning (ML) methods and the Internet of Things (IoT) have been successfully implemented in medical research to improve the diagnosis and prevention of complex diseases and syndromes. The goal of this work is to undertake a review of the most recent work on preeclampsia detection. The research focused on articles related to the keywords 'machine learning, 'Internet of Things, 'IoT', 'medical', and preeclampsia in five main databases, namely IEEEXplore, ScienceDirect, SpringerLink, ResearchGate, and ACM Digital Library, etc. We selected and reviewed 90 articles in the end. The final discussion highlights research gaps that remain to be investigated in the cognitive approach to IoT. The study found that preeclampsia detection based on the internet of Medical things (IoMT) was not found, so it became a big opportunity to develop this research in the future.
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