Blood pressure (BP) estimation is one of the most popular and long-standing topics in health-
care monitoring area. The utilization of machine learning (ML) and deep learning (DL) for BP …

This review describes the steps and conclusions from the development and validation of an
artificial intelligence algorithm (the Hypotension Prediction Index), one of the first machine …

This paper refers to the method of using the deep neural long-short-term memory (LSTM)
network for the problem of electrocardiogram (ECG) signal classification. ECG signals …

Hypotensive events in the initial stage of anesthesia can cause serious complications in the
patients after surgery, which could be fatal. In this study, we intended to predict hypotension …

Arterial hypotension is associated with incidence of postoperative complications, such as
myocardial infarction or acute kidney injury. Little research has been conducted for the real …

Recently, research has been conducted to automatically control anesthesia using machine
learning, with the aim of alleviating the shortage of anesthesiologists. In this study, we …

Abstract Predicting Bispectral Index (BIS) and Mean Arterial Pressure (MAP) during
anesthesia is critical for patient safety and effective anesthesia management. Traditional …

Artificial intelligence (AI) has recently become a ubiquitous term, occurring frequently in as
diverse media as newspapers to political debates to medical articles. However, there is often …

The monitoring of arterial blood pressure (ABP) in anesthetized patients is crucial for
preventing hypotension, which can lead to adverse clinical outcomes. Several efforts have …

Intraoperative hypotension (IOH) events warning plays a crucial role in preventing
postoperative complications, such as postoperative delirium and mortality. Despite …