Artificial Intelligence Medical Compendium

Sidestream struvite recovery systems can significantly enhance the performance of mainstream biological phosphorus (P) removal processes by reducing intraplant P cycling from solids handling return flows. While adoption of struvite recovery systems h... read more 

Accurate identification of anomalies and reconstruction of missing data are crucial for the intelligent operation of industrial park wastewater treatment plants (WWTPs). However, traditional statistical and model-based approaches often fall short in ... read more 

Phosphorus (P) is a vital macronutrient for plant growth, but its limited availability in soil due to fixation renders up to 80 % of fertilizers ineffective. Visual symptoms for P deficiency appear late or remain inconclusive, complicating timely int... read more 

This paper investigates the bipartite synchronization problem of competitive-cooperative inertial neural networks (CCINNs) with time-varying delays under a composite control strategy. The main challenge lies in simultaneously addressing the complex c... read more 

The rapid development of deep learning provides an excellent solution for end-to-end multi-modal image fusion. However, existing methods mainly focus on the spatial domain and fail to fully utilize valuable information in the frequency domain. Moreov... read more 

The use of heterogeneous networks has gained significant traction for modeling and analyzing complex systems across diverse domains because of their ability to represent various types of entities and relationships. However, these networks face consid... read more 

Rock glaciers, periglacial landforms with tongue- or lobe-shaped streams of slowly deforming frozen debris, play an important role in periglacial mountainous regions. The understanding of rock glaciers and their geoecological role at regional scales ... read more 

Early detection of anomalies in medical images such as brain magnetic resonance imaging (MRI) is highly relevant for diagnosis and treatment of many medical conditions. Supervised machine learning methods are limited to a small number of pathologies ... read more 

Coral reef ecosystems are increasingly threatened by climate change and human activities, and conservation organizations worldwide require efficient, cost-effective tools to document habitat conditions, assess artificial reef growth, and monitor cora... read more 

Existing traffic conflict models face challenges in handling minority class samples and capturing dynamic interactions in complex traffic scenarios. These limitations hinder model generalization and real-world applicability. This study employs an enh... read more