Artificial Intelligence Medical Compendium

Rhinosinusitis is a spectrum of diseases with varied causes, presentations, and diagnostic approaches-from viral and bacterial acute rhinosinusitis to chronic inflammatory or fungal etiologies. This article reviews the diagnosis of acute, chronic, re... read more 

PURPOSE: To compare associations between 90-day vision and microbial keratitis-related corneal changes when predicted by an artificial intelligence image-based algorithm or when measured by a clinician. METHODS: This prospective cohort study followed... read more 

In daily life, emotions tend to exhibit amalgamated forms. For instance, when someone is involved in an interview, excitement and nervousness consistently coexist. In previous studies on empathetic dialogue, the mixed emotions in the conversation hav... read more 

Deep learning models demonstrate vulnerability to textual adversarial attacks. Research on adversarial text generation methods contributes to the subsequent design of corresponding countermeasures. Current word-level adversarial text generation metho... read more 

Most existing Image-to-Image Translation (I2IT) methods generate images in a single run of deep learning (DL) models. However, designing a single-step model often requires many parameters and suffers from overfitting. Inspired by the analogy between ... read more 

This article presents a methodological breakthrough in supervised learning for training a single, robust, and high-performance artificial intelligence (AI) model using a multitude of datasets labeled differently-yet requiring no manual label harmoniz... read more 

Chronic wasting disease (CWD) is a contagious neurodegenerative disease in cervids and its spread threatens the health of wild and farm-raised animals. A rapid screening method for CWD is in great demand. Compared to current diagnostic methods, ELISA... read more 

Using machine learning (ML) and deep learning (DL) algorithms for precise coagulant dosing in drinking water treatment plants (DWTPs) helps ensure drinking water safety and supports greenhouse gas (GHG) emission reduction. The effectiveness of these ... read more 

In deep metric learning, proxy-based losses aim to introduce proxy representations to approximate class distributions, reducing training complexity and accelerating model convergence. Existing proxy-based losses can be broadly categorized into two ty... read more 

The resilience of autonomous unmanned swarms (AUS) serves as a cornerstone for guaranteeing continuous mission execution in the face of adversarial interferences. Contemporary methodologies often suffer from limited generalization efficacy and volati... read more