This study systematically examined the impact of three feature selection techniques (Boruta, Extreme gradient boosting (XGBoost), and Lasso) for optimizing four machine learning models (Random forest (RF), XGBoost, Logistic regression (LR), and Suppo...
AIM: To assess the predictive performance, risk stratification capabilities, and auxiliary diagnostic utility of radiomics, deep learning, and fusion models in identifying visceral pleural invasion (VPI) in lung adenocarcinoma.
BACKGROUND: There is a lack of studies exploring the performance of Transformers-based language models in common risks assessment among psychiatric inpatients. We aim to develop a scalable risk assessment model using multidimensional textualized data...
The growing adoption of Artificial Intelligence (AI) across sectors highlights the importance of diverse perspectives in guiding its development and implementation. This study examines"Datawiz-IN" an educational initiative that provides data science ...
BACKGROUND: Generative artificial intelligence (generative AI) has revolutionized the healthcare system for medical students and their educational process worldwide. Several studies assessed its efficacy in improving medical studies learning, and oth...
BACKGROUND: Cervical cancer remains a significant global health issue, with accurate differentiation between low-grade (LSIL) and high-grade squamous intraepithelial lesions (HSIL) crucial for effective screening and management. Current methods, such...
SAPHO syndrome is an inflammatory disorder with bone and cutaneous manifestations, for which whole-body bone scintigraphy (WBBS) is frequently used in diagnosis. The WBBS findings of SAPHO syndromes and secondary bone tumors (SBT) have overlapping fe...
Fluoroscopically guided electrophysiology (EP) procedures expose operators to low doses of ionizing radiation, which can induce DNA double-strand breaks (DSBs) and raises increasing concerns regarding potential health risks. A novel robotic radiation...
To compare the diagnostic accuracy of an artificial intelligence chatbot and clinical experts in vertigo-related diseases and evaluate the ability of the AI chatbot to address vertigo-related issues. 20 clinical questions about vertigo were input to ...
As populations age, understanding cognitive decline and age-related diseases like dementia has become increasingly important. "SuperAgers," individuals over 65 with cognitive abilities similar to those in their 40s, provide a unique perspective on co...
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