Why today’s AI systems struggle with consistency and how emerging world models aim to give machines a steady grasp of space ...
Abstract: The manual diagnosis of diabetic retinopathy (DR) is often invasive, time-consuming, expensive, and prone to human error. Additionally, it can be subjective ...
Background: The diagnosis of occupational pneumoconiosis requires more accurate predictive models. The purpose of this study is to screen blood markers associated with early pneumoconiosis development ...
Objective: This study aims to identify the key risk factors for occupational exposure among oral healthcare workers and develop a predictive model using machine learning algorithms to lay the ...
Abstract: Flower classification is a challenging task in computer vision, requiring models to discern subtle visual differences among a vast array of floral species. In this project, we propose a ...