Artificial Intelligence Medical Compendium

In clinical practice, magnetic resonance imaging is essential for disease diagnosis and evaluation, although it generally requires a prolonged scanning duration. Recently, several deep learning-based restoration techniques have been introduced to acc... read more 

Congenital anomalies of the kidney and urinary tract (CAKUT) are the major cause of childhood chronic kidney disease and an antecedent cause of adult-onset cardiovascular and kidney failure. Both genetic and environmental factors have been implicated... read more 

Exome sequencing (ES) has transformed genomic research and clinical diagnostics by enabling precise identification of disease-associated variants within protein-coding regions, which, while representing a minority of the genome, include many well-cha... read more 

Heatwaves increasingly impact ecosystems, human health, and economic activities worldwide. As their frequency and intensity rise, understanding the mechanisms driving heatwave dynamics and interactions with land surface processes becomes crucial. Whi... read more 

Algal blooms, characterized by the excessive proliferation of microalgae in a freshwater or marine ecosystem, have evolved into a global ecological, health and economic crisis, which is often accompanied by the release of toxins and the damage of the... read more 

Invasive freshwater snails of the family Ampullariidae present significant threats to agriculture, biodiversity, and public health. Recent advances in deep learning have enabled automated identification of medically and agriculturally important snail... read more 

This study investigates the shared molecular mechanisms between major depressive disorder (MDD) and systemic lupus erythematosus (SLE) through integrated bioinformatics analysis. Analysis of multiple GEO datasets identified 23 common differentially e... read more 

Accurate detection of tumor boundaries is critical for the success of oncologic surgical intervention. Traditionally, palpation can handover important information for tumor localization based on the tissue mechanical properties, but in Minimally Inva... read more 

The vulnerability of Deep Neural Networks (DNNs) to black-box adversarial attacks remains a pressing issue in modern Automatic Speech Recognition (ASR) systems. Although existing query-based methods, which combine genetic algorithms (GAs) with gradie... read more 

To obtain better value estimation in reinforcement learning, we propose a novel algorithm based on the double actor-critic framework with temporal difference error-driven regularization, abbreviated as TDDR. TDDR employs double actors, with each acto... read more