Discovering topics and trends in the field of Artificial Intelligence: Using LDA topic modeling

D Yu, B Xiang - Expert systems with applications, 2023 - Elsevier
Artificial Intelligence (AI) has affected all aspects of social life in recent years. This study
reviews 177,204 documents published in 25 journals and 16 conferences in the AI research …

A systematic literature review and future perspectives for handling big data analytics in COVID-19 diagnosis

N Tenali, GRM Babu - New Generation Computing, 2023 - Springer
In today's digital world, information is growing along with the expansion of Internet usage
worldwide. As a consequence, bulk of data is generated constantly which is known to be …

[HTML][HTML] A new approach to predicting mortality in dialysis patients using sociodemographic features based on artificial intelligence

C Díez-Sanmartín, AS Cabezuelo… - Artificial Intelligence in …, 2023 - Elsevier
One of the main problems that affect patients in dialysis therapy who are on the waiting list to
receive a kidney transplant is predicting their survival time if they do not receive a transplant …

Impact of artificial intelligence on customer engagement and advertising engagement: A review and future research agenda

C Suraña‐Sánchez… - International Journal of …, 2024 - Wiley Online Library
This study, through a bibliometric analysis, aims to provide increased knowledge of the
evolution and effects of artificial intelligence over the last 30 years in customer engagement …

Artificial intelligence in kidney disease: a comprehensive study and directions for future research

CC Wu, MM Islam, TN Poly, YC Weng - Diagnostics, 2024 - mdpi.com
Artificial intelligence (AI) has emerged as a promising tool in the field of healthcare, with an
increasing number of research articles evaluating its applications in the domain of kidney …

[HTML][HTML] Ensemble of machine learning techniques to predict survival in kidney transplant recipients

C Díez-Sanmartín, AS Cabezuelo… - Computers in Biology and …, 2024 - Elsevier
Kidney transplant recipients face a high cardiovascular risk, which is a leading cause of
death in this patient group. This article proposes the application of clustering techniques and …

Revolutionizing Kidney Transplantation: Connecting Machine Learning and Artificial Intelligence with Next-Generation Healthcare—From Algorithms to Allografts

L Ramalhete, P Almeida, R Ferreira, O Abade… - …, 2024 - mdpi.com
This review explores the integration of artificial intelligence (AI) and machine learning (ML)
into kidney transplantation (KT), set against the backdrop of a significant donor organ …

Conceptual metaphor quantum correlation and radial basis extreme learning for predicting chronic kidney disease

M Jayashree, N Anitha - Computers and Electrical Engineering, 2025 - Elsevier
Chronic kidney disease is a progressive condition that often remains unnoticed until
substantial kidney damage has occurred, leading to severe complications like nerve …

Extracting Decision Paths via Surrogate Modeling for Explainability of Black Box Classifiers

J Rad, K Tennankore, S Abidi… - 2024 11th IEEE Swiss …, 2024 - ieeexplore.ieee.org
A common challenge in using intricate machine learning (ML) classifiers in critical domains
is the lack of transparency in making predictions despite exhibiting high performance …

A REST API based on machine learning to predict survival using categorical features

C Díez-Sanmartín… - 2023 27th International …, 2023 - ieeexplore.ieee.org
Survival analysis is an area of statistics that deals with the study of the time it takes for an
event of interest to occur, usually applying mainstream statistical techniques. The …