BACKGROUND AND OBJECTIVES: Assessing and improving academic writing skills is a crucial component of higher education. To support students in this endeavor, a comprehensive self-assessment toolkit was developed to provide personalized feedback and gu...
Halitosis presents a significant global health concern, necessitating the development of precise and efficient testing methodologies owing to the high prevalence and the associated social and psychological effects. The measurement of volatile sulfur ...
BACKGROUND: Although recreational drug use is a strong risk factor for acute cardiovascular events, systematic testing is currently not performed in patients admitted to intensive cardiac care units, with a risk of underdetection. To address this iss...
Tumor cellularity (TC) in lung adenocarcinoma slides submitted for molecular testing is important in identifying actionable mutations, but lack of best practice guidelines results in high interobserver variability in TC assessments. An artificial int...
OBJECTIVES: This study aimed to evaluate the effectiveness of large language models (LLM) in assessing the methodological quality of radiomics research, using METhodological RadiomICs Score (METRICS) tool.
PURPOSE: This study aims to assess whether the novel CovBat harmonization method can further reduce radiomics feature variability from different imaging devices in multi-center studies and improve machine learning model performance compared to the Co...
The international journal of cardiovascular imaging
Jan 29, 2025
Artificial intelligence-based quantitative coronary angiography (AI-QCA) was introduced to address manual QCA's limitations in reproducibility and correction process. The present study aimed to assess the performance of an updated AI-QCA solution (MP...
BACKGROUND: The rapid evolution of large language models (LLMs), such as Bidirectional Encoder Representations from Transformers (BERT; Google) and GPT (OpenAI), has introduced significant advancements in natural language processing. These models are...
BACKGROUND: Early detection and diagnosis of cancer are vital to improving outcomes for patients. Artificial intelligence (AI) models have shown promise in the early detection and diagnosis of cancer, but there is limited evidence on methods that ful...