Artificial Intelligence Medical Compendium

OBJECTIVES: Carbohydrate counting is a recommended approach for achieving glycemic control in individuals with type 1 diabetes (T1D). This study aimed to compare the accuracy of carbohydrate content estimations for traditional Turkish fast foods made... read more 

INTRODUCTION: More than 100 million individuals in rural areas of China are suffered from Fatty Liver Disease (FLD). However, health clinics in remote regions often lack the necessary professional expertise and expensive ultrasound equipment for regu... read more 

With the widespread use of pesticides and antibiotics in agriculture and healthcare, their associated environmental pollution and potential health hazards have emerged as a global concern. This study presents a novel deep learning-based spectral imag... read more 

Multi-view clustering remains a challenging task due to the heterogeneity and inconsistency across multiple views. Most esisting multi-view spectral clustering methods adopt a two-stage approch-constructing fused spectral embeddings matrix followed b... read more 

Retinal diseases are a leading cause of vision impairment and blindness, with timely diagnosis being critical for effective treatment. Optical Coherence Tomography (OCT) has become a standard imaging modality for retinal disease diagnosis, but OCT im... read more 

Deep neural networks are notoriously vulnerable to adversarial perturbations, largely due to the presence of non-robust features that destabilize model performance. Traditional Adversarial Training (AT) methods on feature space typically operate on o... read more 

Despite the hinge loss function being non-strongly-convex and non-strongly smooth, we establish the linear rate of convergence for sparse linear support vector machines (SVM) up to its statistical accuracy. The algorithm we use is the proximal gradie... read more 

Forest fire smoke detection is crucial for early warning and emergency management, especially under complex environmental conditions such as low contrast, high transparency, background interference, low illumination, occlusion, and overlapping smoke ... read more 

This paper is dedicated to demonstrating the influence of leaders on followers in signed networks with antagonistic interactions, where leaders have their own dynamics and interact with other leaders in a strongly connected closed subgraph (SCCC). An... read more 

Existing bipartite graph based methods commonly learn a consistent anchor graph across multiple views utilizing various optimization techniques to determine clustering assignments, maintaining linear complexity w.r.t. the number of samples. Owing to ... read more