This review paper examines the transformative role of artificial intelligence (AI) and dynamic
ensemble techniques in enhancing healthcare services. By systematically reviewing …

Due to huge investments by both the public and private sectors, artificial intelligence (AI) has
made tremendous progress in solving multiple real-world problems such as disease …

Data play a key role in AI systems that support decision-making processes. Data-centric AI
highlights the importance of having high-quality input data to obtain reliable results …

With the advancement of big data, the scope and potential of Artificial Intelligence (AI) have
acquired major momentum. Data-Centric Artificial Intelligence (DCAI) is one of the most …

Artificial intelligence-enabled business models aim to improve decision-making, operational
efficiency, innovation, and productivity. The presented systematic literature review is …

Reliable simulations are critical for analyzing and understanding complex systems, but their
accuracy depends on correct input data. Incorrect inputs such as invalid or out-of-range …

Most artificial intelligence (AI) applications are designed under the model-centric AI (MCAI)
approach, where data scientists aim to optimize the machine learning (ML) models starting …

In the fast-evolving field of data science, the combination of the right team competencies has
a major impact on a successful project execution. These competencies, ranging from data …

Data preparation has an important role in data analysis, and it is time and resource-
consuming, both in terms of human and computational resources. The" Discount quality for …

Data preparation is the first and a very important step towards any Large Language Model
(LLM) development. This paper introduces an easy-to-use, extensible, and scale-flexible …