This work intends to drive reform and innovation in English teaching evaluation and support personalized English instruction. It utilizes deep learning (DL) and artificial intelligence (AI)-driven data mining technology to explore a reliable and effi...
The respiratory virus known as human metapneumovirus (hMPV) is linked to seasonal outbreaks and primarily affects elderly people and young children. Infodemiology, which uses digital data sources, including social media, online news, and search trend...
Exploring students' cognitive abilities has long been an important topic in education. This study employs data-driven artificial intelligence (AI) models supported by explainability algorithms and PSM causal inference to investigate the factors influ...
To evaluate scientific literature regarding the application of Photobiomodulation (PBM), with a special focus on Multiwave Locked System (MLS) laser therapy, an innovative machine learning method was used. PBM therapy has occurred as a non-invasive t...
Drug repurposing accelerates microbial therapy development by bypassing the costly and time-consuming traditional drug discovery process. However, existing computational methods for predicting drug-microbe associations (MDAs) struggle to capture comp...
With the integration of educational technology and artificial intelligence, personalized learning has become increasingly important. However, traditional educational data mining methods struggle to effectively integrate heterogeneous feature data and...
BACKGROUND: Rare diseases often present with a variety of clinical symptoms and therefore are challenging to diagnose. Fabry disease is an x-linked rare metabolic disorder. The severity of symptoms is usually different in men and women. Since therape...
This study proposes a novel approach to anticipating technology convergence in the bio-healthcare sector by integrating text mining based on transformer models and supervised learning methodologies. The overarching goal is to develop a robust method ...
Automatic phenotype extraction and assertion negation detection from large-scale accessible Electronic Health Records (EHRs), including discharge summaries and radiology reports, is a crucial task for various healthcare applications, such as disease ...
Understanding acute heart failure (AHF) remains a significant challenge, as many clinical details are recorded in unstructured text rather than structured data in electronic health records (EHRs). In this study, we explored the use of large language ...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.