Machine Learning and Knowledge Extraction, Volume 5, Issue 3

Typically, renewable-power-generation forecasting using machine learning involves creating separate models for each photovoltaic or wind park, known as single-task learning models. However, transfer learning has gained popularity in recent years, as...

Thyroid disease is among the most prevalent endocrinopathies worldwide. As the thyroid gland controls human metabolism, thyroid illness is a matter of concern for human health. To save time and reduce error rates, an automatic, reliable, and accurate...

One of the challenges in deep learning involves discovering the optimal architecture for a specific task. This is effectively tackled through Neural Architecture Search (NAS). Neural Architecture Search encompasses three prominent approaches—re...

Massive text collections are the backbone of large language models, the main ingredient of the current significant progress in artificial intelligence. However, as these collections are mostly collected using automatic methods, researchers have few i...

Social networks have captured the attention of many people worldwide. However, these services have also attracted a considerable number of malicious users whose aim is to compromise the digital assets of other users by using messages as an attack vec...

(1) Background: Avatar Therapy (AT) is currently being studied to help patients suffering from treatment-resistant schizophrenia. Facilitating annotations of immersive verbatims in AT by using classification algorithms could be an interesting avenue...

Dimensionality reduction methods can be used to project high-dimensional data into low-dimensional space. If the output space is restricted to two dimensions, the result is a scatter plot whose goal is to present insightful visualizations of distance...

Predicting emissions for gas turbines is critical for monitoring harmful pollutants being released into the atmosphere. In this study, we evaluate the performance of machine learning models for predicting emissions for gas turbines. We compared an ex...

The concept of a digital twin (DT) has gained significant attention in academia and industry because of its perceived potential to address critical global challenges, such as climate change, healthcare, and economic crises. Originally introduced in m...

This study examines the ethical issues surrounding the use of Artificial Intelligence (AI) in healthcare, specifically nursing, under the European General Data Protection Regulation (GDPR). The analysis delves into how GDPR applies to healthcare AI p...