Latest AI and machine learning research in smoking & tobacco for healthcare professionals.
As vision-based machine learning models are increasingly integrated into autonomous and cyber-phys...
INTRODUCTION: Tobacco companies use social media to bypass marketing restrictions. Studies show that...
Colorectal cancer remains a major health concern, with colorectal polyps as key precursors. Endoscop...
Knowledge distillation (KD) is a valuable technique for compressing large deep learning models int...
Vision Mamba has recently emerged as a promising alternative to Transformer-based architectures, o...
Multimodal pathology-genomic analysis has become increasingly prominent in cancer survival predict...
The forecasting of irregular multivariate time series (IMTS) is crucial in key areas such as healt...
Prostate cancer is a leading cause of cancer-related deaths, with Gleason grading being key for asse...
Accurately documenting smoking status is essential for clinical decision-making and patient care. Ho...
Real-time monitoring of sweat using wearable devices faces challenges such as limited adhesion, mech...
Whole slide image (WSI) classification has emerged as a powerful tool in computational pathology, ...
Tertiary lymphoid structures (TLS) are organized clusters of immune cells, whose maturity and area...
Low-rank matrix approximation (LoRMA) is a fundamental tool for compressing high-resolution data m...
This study investigates changes in resting-state networks (RSNs) associated with tobacco addiction (...
Forensic genetics has experienced remarkable advancements over the past decades, evolving from the a...
Accurate blood glucose prediction can enable novel interventions for type 1 diabetes treatment, in...
Visual Document Retrieval (VDR) is an emerging research area that focuses on encoding and retrievi...
Breast-conserving surgery (BCS) aims to completely remove malignant lesions while maximizing healt...
Smoking has been widely identified for its detrimental effects on human health, particularly on the ...
Recent progress in image-based medical disease detection encounters challenges such as limited ann...
Most existing text recognition methods are trained on large-scale synthetic datasets due to the sc...