Artificial Intelligence Medical Compendium

Polysaccharides, the most abundant natural biopolymers, exhibit outstanding biocompatibility and versatile functionality, making them valuable for applications in food, biomedicine and sustainable packaging. However, their native forms often suffer f... read more 

Artificial intelligence (AI) is gradually altering urology by improving diagnostic precision, prognostic evaluation, and therapy decisions in a broad spectrum of urologic diseases. Utilizing machine learning, deep learning, and radiomics, application... read more 

Laser-Induced Breakdown Spectroscopy (LIBS) holds significant value for rapid elemental detection; however, strong spectral interference, matrix effects, and high-dimensional data characteristics pose considerable challenges to accurate quantitative ... read more 

Low-light images often suffer from complex degradation factors such as reduced contrast, color distortion, and noise. Recently, progressive networks have gained great popularity in low-light image enhancement due to their strong ability to recover im... read more 

Phenol is a vital chemical precursor in modern industry; however, the dominant cumene process for its production generates wastewater laden with complex organic compounds, making the accurate detection of phenol critically important. Traditional spec... read more 

OBJECTIVE: This study aims to develop a low-dose CT-based, fully automated deep learning tool for screening adrenal gland volume abnormalities and establishing personalized reference ranges to assist in diagnosing adrenal diseases. METHODS: This stud... read more 

As the volume of governance text data continues to grow, agile governance requires the rapid and accurate extraction of actionable information from large data streams while maintaining the effectiveness of Named Entity Recognition (NER) models in dyn... read more 

Data Augmentation (DA) aims to create a new dataset to address the lack of data in various domains. Particularly in few-shot scenarios of the biomedical Named Entity Recognition (NER) domain, an effective DA method can enhance data diversity, reduce ... read more 

Early detection of Alzheimer's disease (AD) is essential for effective clinical intervention and disease management. However, conventional Deep Learning (DL) methods face limitations in analyzing complex brain magnetic resonance imaging (MRI), especi... read more 

Advancements in neuroimaging have facilitated unprecedented insights into brain connectivity, making the study of brain effective connectivity networks (ECNs) essential for understanding neurological functions and diseases. Recently, neural networks ... read more