Artificial Intelligence Medical Compendium

Soil pollution threatens human health and food security, particularly in industrial legacy sites. Accurate three-dimensional distribution modeling of soil contamination is crucial for understanding pollutant migration and guiding targeted remediation... read more 

BACKGROUND & AIMS: We aimed to identify subgroups of patients with unresectable hepatocellular carcinoma (HCC) using a non a priori, data-driven machine learning approach to uncover subgroups with distinct profiles across a range of clinical and tumo... read more 

The study investigates the application of Artificial Intelligence (AI) driven neural network time series (NNTS) model for the forecasting prediction of dye removal using ultrasonic activated mixed biomass. Surface and functional characterization of u... read more 

The oral microbiome is shaped by environmental and host-associated factors, suggesting its utility for human profiling in forensics, particularly as an indicator of geographic origin and human migration. Using high-throughput sequencing and machine l... read more 

The invasiveness prediction in renal cell carcinoma (RCC) is of significant importance for the decision of clinical surgical plans and the patients' prognosis. Currently, besides invasive pathological assessment, it mainly relies on observation throu... read more 

Artificial intelligence (AI) is rapidly transforming scientific disciplines, yet its adoption in food science remains fragmented and often constrained to narrow application scenarios. This perspective provides a practical guide for food scientists to... read more 

Spatial transcriptomics is a technology that captures gene expression at different spatial locations, widely used in tumor microenvironment analysis and molecular profiling of histopathology, providing valuable insights into resolving gene expression... read more 

The food industry is continually evolving, driven by the demand for innovative processing technologies capable of preserving the nutritional and functional properties while ensuring food safety and quality. Traditional thermal processing frequently r... read more 

The rapid development of large language models (LLMs) has accelerated research into applying artificial intelligence (AI) to domains such as medical question answering and clinical decision support. However, LLMs face substantial limitations in medic... read more 

Activation functions are essential in deep learning optimization for introducing non-linearity, shaping gradient dynamics, and influencing weight initialization. This paper presents a modified Gaussian function called R-Gaussian, an activation functi... read more