Artificial Intelligence Medical Compendium

The pathological grading of cervical squamous cell carcinoma (CSCC) is a fundamental and important index in tumor diagnosis. Pathologists tend to focus on single differentiation areas during the grading process. Existing multi-instance learning (MIL)... read more 

Artificial intelligence (AI) is rapidly transforming dermatology, particularly through diagnostic imaging and enhancing patient management. Despite expanding clinical applications, public engagement with AI in dermatology remains underexplored. This ... read more 

OBJECTIVE: This study aimed to systematically evaluate the efficacy of robot-assisted training (RAT) in improving the physical rehabilitation outcomes of burn patients and to establish a clinical basis for its broader application. METHODS: Randomized... read more 

CONTEXT: Pediatric Emergency Departments (PEDs) face overcrowding partially due to delayed hospital admission decision. Machine Learning (ML) models could early predict it. OBJECTIVE: To systematically review and critically appraise the development, ... read more 

The extended dissipativity issue for delayed markovian jump neural networks (MJNNs) with partially unknown transition rates (PUTRs) is investigated. Unlike conventional Lyapunov-Krasovskii functional (LKF), where positive-definite constraint is direc... read more 

Accurate metabolite identification remains a major challenge in untargeted metabolomics, particularly for novel compounds that are absent from existing spectral libraries. In this work, we propose a novel Feature Fusion Network (FFNet) based on Trans... read more 

Antibiotic failure has emerged as a critical global health concern, driven by a combination of factors including the stagnation in the discovery of new antibiotics, the widespread emergence of resistance mechanisms among clinical bacterial isolates, ... read more 

Artificial Neural Networks (ANNs) have significantly advanced various fields by effectively recognizing patterns and solving complex problems. Despite these advancements, their interpretability remains a critical challenge, especially in applications... read more 

BACKGROUND: Manual interpretation of brain tumor regions in MRI scans demands substantial medical expertise, is time-consuming, and is prone to human error, especially when radiologists must review large scan volumes, leading to fatigue and reduced d... read more 

INTRODUCTION: The United States Food and Drug Administration (FDA) requires post-marketing surveillance of approved drugs, and pharmaceutical manufacturers maintain comprehensive programs that include adverse event monitoring, internal safety assessm... read more