[HTML][HTML] Bio-signals in medical applications and challenges using artificial intelligence
Artificial Intelligence (AI) has broadly connected the medical field at various levels of
diagnosis based on the congruous data generated. Different types of bio-signal can be used …
diagnosis based on the congruous data generated. Different types of bio-signal can be used …
[HTML][HTML] Machine-learning-based emotion recognition system using EEG signals
R Alhalaseh, S Alasasfeh - Computers, 2020 - mdpi.com
Many scientific studies have been concerned with building an automatic system to recognize
emotions, and building such systems usually relies on brain signals. These studies have …
emotions, and building such systems usually relies on brain signals. These studies have …
Distributed model for customer churn prediction using convolutional neural network
Purpose The purpose of the proposed model is to assist the e-business to predict the
churned users using machine learning. This paper aims to monitor the customer behavior …
churned users using machine learning. This paper aims to monitor the customer behavior …
Machine Learning Application in Horticulture and Prospects for Predicting Fresh Produce Losses and Waste: A Review
The current review examines the state of knowledge and research on machine learning (ML)
applications in horticultural production and the potential for predicting fresh produce losses …
applications in horticultural production and the potential for predicting fresh produce losses …
[HTML][HTML] An integrated machine learning and DEMATEL approach for feature preference and purchase intention modelling
This article models the purchasing intention of young Indian consumers for branded
smartphones by analysing their individual preferences for the different features of the …
smartphones by analysing their individual preferences for the different features of the …
[HTML][HTML] A Consumer Behavior Analysis Framework toward Improving Market Performance Indicators: Saudi's Retail Sector as a Case Study
M Alawadh, A Barnawi - Journal of Theoretical and Applied Electronic …, 2024 - mdpi.com
Studying customer behavior and anticipating future trends is a challenging task, as customer
behavior is complex and constantly evolving. To effectively anticipate future trends …
behavior is complex and constantly evolving. To effectively anticipate future trends …
An integration of blockchain and machine learning into the health care system
MS Arza, SK Panda - Machine Learning Adoption in Blockchain …, 2022 - taylorfrancis.com
Currently, machine learning and blockchain play a predominant role in the health care
sector. In health care, machine learning is most commonly used for administrative purposes …
sector. In health care, machine learning is most commonly used for administrative purposes …
Comparison of the performance of machine learning techniques in the prediction of employee
Human Resources' purpose is to assign the best people to the right job at the right time, train
and qualify them, and provide evaluation methods to track their performance and safeguard …
and qualify them, and provide evaluation methods to track their performance and safeguard …
AI in consumer behavior
DC Gkikas, PK Theodoridis - … Technologies: Selected Papers in Honour of …, 2022 - Springer
E-commerce is one of the fastest changing industries and consumers try to purchase most of
the goods online. Following the internet revolution, retail and promotion, daily data …
the goods online. Following the internet revolution, retail and promotion, daily data …
Effective information retrieval and feature minimization technique for semantic web data
CSS Kumar, R Santhosh - Computers & Electrical Engineering, 2020 - Elsevier
The Internet contains both structured and unstructured data. The enormous flow of Internet
data creates challenges in relation to effective information retrieval. Semantic Web Mining …
data creates challenges in relation to effective information retrieval. Semantic Web Mining …