Artificial Intelligence Medical Compendium

In this paper, we investigate the applications of operator learning, specifically DeepONet, for solving nonlinear partial differential equations (PDEs). Unlike conventional function learning methods that require training separate neural networks for ... read more 

Accurate prediction of groundwater heavy metal contaminant spatiotemporal dynamics is essential for monitoring optimization and remediation decision-making at contaminated sites. However, heterogeneous contamination distribution and complex spatiotem... read more 

Aiming to address the dynamic prediction challenge of space battlefield targets, this paper proposes a hybrid prediction model integrating fuzzy cognitive map (FCM) and echo state networks (ESN). The model first constructs a fuzzy relation map of ene... read more 

BACKGROUND: Botulism is a rare but potentially fatal illness caused by botulinum neurotoxin, with outbreaks reported globally in humans, animals, and the environment. In the absence of a global surveillance system, open-source intelligence (OSINT) of... read more 

Spiking Neural Networks (SNNs) are biologically-inspired deep neural networks that efficiently extract temporal information while offering promising gains in terms of energy efficiency and latency when deployed on neuromorphic devices. SNN parameters... read more 

This article examines the transformative potential of ProSocial Artificial Intelligence (AI) in revolutionizing oral health care. ProSocial AI emphasizes prevention over treatment, empowering patients through autonomy, personalized support, and share... read more 

Oral medicine is the dental specialty dedicated to the oral health care of medically complex patients and the diagnosis and management of medically related diseases, disorders, and conditions affecting the oral and maxillofacial region. Like other de... read more 

In neurosurgery, accurate brain tissue characterization via probe-based Confocal Laser Endomicroscopy (pCLE) has become popular for guiding surgical decisions and ensuring safe tumour resections. In order to enable surgeons to trust a tissue classifi... read more 

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Physics-informed machine learning (PIML) has emerged as a promising alternative to classical methods for predicting dynamical systems, offering faster and more generalizable solutions. However, existing models, including recurrent neural networks (RN... read more