The rise of Large Language Models (LLMs), such as LLaMA and ChatGPT, has opened new opportunities for enhancing recommender systems through improved explainability. This paper provides a systematic literature review focused on leveraging LLMs to gene...
INTRODUCTION: Ambient acoustic detection and localization play a vital role in identifying events and their origins from acoustic data. This study aimed to establish a comprehensive framework for classifying activities in home environments to detect ...
Advances in high-throughput genome sequencing have enabled large-scale genome sequencing in clinical practice and research studies. By analyzing genomic variants of humans, scientists can gain better understanding of the risk factors of complex disea...
BACKGROUND: Leukemia is the 11 most prevalent type of cancer worldwide, with acute myeloid leukemia (AML) being the most frequent malignant blood malignancy in adults. Microscopic blood tests are the most common methods for identifying leukemia subty...
Predicting the dynamics of chaotic systems is crucial across various practical domains, including the control of infectious diseases and responses to extreme weather events. Such predictions provide quantitative insights into the future behaviors of ...
Atmospheric ozone chemistry involves various substances and reactions, which makes it a complex system. We analyzed data recorded by Switzerland's National Air Pollution Monitoring Network (NABEL) to showcase the capabilities of machine learning (ML)...
The emergence of advanced artificial intelligence (AI) models has driven the development of frameworks and approaches that focus on automating model training and hyperparameter tuning of end-to-end AI pipelines. However, other crucial stages of these...
INTRODUCTION: Self-efficacy is a critical determinant of students' academic success and overall life outcomes. Despite its recognized importance, research on predictors of self-efficacy using machine learning models remains limited, particularly with...