Artificial Intelligence Medical Compendium

BACKGROUND: The pathogenesis of keloids is still unclear and effective biomarkers are lacking. Therefore, it is urgent to find clinically effective biomarkers and study their regulatory mechanisms. METHODS: Candidate genes were screened by amplifying... read more 

Self-attention is the cornerstone of transformers, yet its quadratic time and space complexity with respect to the input sequence length leads to high training costs. To mitigate this issue, various linear self-attention methods have been proposed. H... read more 

Underwater moving target tracking with sonar device is very challenging. Due to complex underwater environment, sonar acquired videos have domain-specific challenges like texture-similar backgrounds and variable visual attributes, impairing the perfo... read more 

BACKGROUND AND OBJECTIVE: Accurate disease diagnosis is vital for effective treatment and improved patient outcomes. While artificial intelligence (AI) has advanced medical diagnostics, conventional AI approaches often face limitations in real-time d... read more 

Unlike the prevalent image classification paradigm that assumes all samples belong to pre-defined classes, Open set recognition (OSR) indicates that new classes unobserved during training could appear in testing. It mandates a model to not only categ... read more 

PURPOSE: To retrospectively assess the agreement between human and automated AI-based readings for low-dose computed tomography (LDCT) outcomes according to LungRADS v1.1 in lung cancer screening (LCS); to test the diagnostic performance of both read... read more 

OBJECTIVES: Lower extremity fractures are prevalent in vulnerable populations leading to significant burdens, which highlight the need for timely and precise diagnosis. Integrating deep learning with imaging findings has shown promising results for e... read more 

Automatic seizure detection holds significant importance for epilepsy diagnosis and treatment. Convolutional neural networks (CNNs) have shown immense potential in seizure detection. Though traditional CNN-based seizure detection models have achieved... read more 

BackgroundAccurate intraoperative blood loss estimation is crucial, particularly for pediatric and adolescent patients. Traditional methods (visual, gravimetric, formula-based) are often imprecise and unreliable, highlighting a need for objective and... read more 

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