6 documents found, page 1 of 1

Predicting consumer ad preferences: leveraging a machine learning approach for ...

This research unveils to predict consumer ad preferences by detecting seven basic emotions, attention and engagement triggered by advertising through the analysis of two specific physiological monitoring tools, electrodermal activity (EDA), and Facial Expression Analysis (FEA), applied to video advertising, offering a twofold contribution of significant value. First, to identify the most relevant physiological ...

Machine learning-based cardiac activity non-linear analysis for discriminating ...

Objective: This study highlights the potential of an Electrocardiogram (ECG) as a powerful tool for early diagnosis of COVID-19 in critically ill patients with limited access to CT–Scan rooms. Methods: In this investigation, 3 categories of patient status were considered: Low, Moderate, and Severe. For each patient, 2 different body positions have been used to collect 2 ECG signals. Then, from each collected si...

Editorial: advances in machine learning approaches and technologies for support...

The nervous system is essential for physical and mental health but is complex and delicate. As it can unfortunately be affected by several progressive diseases, an early diagnosis is often critical for effective treatment (Xu et al., 2022). The diagnosis of nervous system diseases traditionally relies on a combination of clinical examination, imaging and signals tests, and laboratory tests (Siuly and Zhang, 201...

COVID-19 detection by means of ECG, Voice, and X-ray computerized systems: a re...

Since the beginning of 2020, Coronavirus Disease 19 (COVID-19) has attracted the attention of the World Health Organization (WHO). This paper looks into the infection mechanism, patient symptoms, and laboratory diagnosis, followed by an extensive assessment of different technologies and computerized models (based on Electrocardiographic signals (ECG), Voice, and X-ray techniques) proposed as a diagnostic tool f...

Enhancing health and public health through machine learning: decision support f...

Editorial: advances in machine learning approaches and technologies for support...