Artificial Intelligence Medical Compendium

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Quinoa, recognized as a nutritionally dense and functionally versatile food source, necessitates non-destructive approaches for quality attribute assessment. This investigation demonstrates enhanced predictive accuracy for three critical quality para... read more 

In recent years, Transformers have become the dominant neural architecture in the fields of natural language processing and computer vision. The generalization of Transformers to graphs, so-called Graph Transformers, have recently emerged as a promis... read more 

Cross-lingual semantic alignment models facilitate the sharing and utilization of multilingual domain-specific data (e.g., medical, legal), offering cost-effective solutions for improving low-resource language tasks. However, existing methods are cha... read more 

Medical images play a pivotal role in disease diagnosis. Numerous studies on cancer image analysis focus on end-to-end deep neural networks, neglecting the analysis of global topological features in images. In cancer diagnosis, pathological images fr... read more 

To tackle the multi-agent adversarial coordination problem, current multi-agent reinforcement learning (MARL) algorithms primarily depend on team-based rewards to update agent policies. However, they do not fully exploit the spatial relationships and... read more 

An important bottleneck in present-day neuromorphic hardware is its reliance on synaptic addition, which limits the achievable degree of parallelization and thus processing throughput. We present a network of monostable multivibrator timers, whose sy... read more 

Immune dysregulation plays a key role in the deterioration of COVID-19. This study evaluated immune checkpoint molecules (ICMs) as markers of disease severity. Immunophenotyping of 525 hospitalised patients with moderate (n=464) and severe (n=61) COV... read more 

Integrating nanotechnology and artificial intelligence (AI) revolutionizes cancer diagnostics, propelling precision medicine into a transformative era. This review examines state-of-the-art nanobiosensors capable of detecting critical biomarkers-circ... read more 

The integration of artificial intelligence (AI) and machine learning (ML) into laboratory medicine shows promise for advancing diagnostic, prognostic, and decision-support tools; however, routine clinical implementation remains limited and heterogene... read more