Artificial Intelligence Medical Compendium

Locally advanced rectal cancer (LARC) is treated with neoadjuvant chemoradiotherapy (nCRT), but only a minority of patients achieve a pathological complete response (pCR). Predictive biomarkers of response could help guide treatment decisions, yet no... read more 

This study presents BRAIN-META, a reproducible deep learning methodology designed for multi-class brain tumor classification using structural MRI. The proposed approach combines ten hybrid CNN-Vision Transformer (ViT) models with a meta-learning ense... read more 

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BACKGROUND: Risk adjustment models in Medicare Advantage determine annual payments of over $300 billion in public funds to private companies. Policymakers want risk adjustment models that are both accurate and interpretable to ensure appropriate use ... read more 

Wastewater treatment plants (WWTPs) are critical for mitigating anthropogenic contaminants, yet their effectiveness in controlling waterborne pathogens has not been assessed globally. This study presents the first global assessment of Escherichia col... read more 

In the field of network security situational awareness (NSSA), it is challenging to find a usable dataset. Most of the datasets used in existing research papers are outdated, small, publicly unavailable due to the private infrastructure on which they... read more 

CONTEXT: Knee Osteoarthritis (KOA) is a progressive degenerative joint disorder and a major cause of disability worldwide. Radiographic grading using the Kellgren-Lawrence (KL) scale remains the standard diagnostic method, but inherent subjectivity a... read more 

Dysphagia in older adults causes serious complications, and efficient and scalable screenings are needed. This prospective multicenter study developed interpretable machine learning (ML) models for the early identification and staging of dysphagia. N... read more 

The biological clock enables organisms to align their intrinsic rhythms with daily environmental cycles thereby maintaining homeostasis and imparting resilience against metabolic derangements. Endocrine hormones and neural networks are key mediators ... read more 

The aim of this study was to distinguish canine lymphoma from other diseases, particularly reactive lymphoid hyperplasia (RLH), based on fine needle aspiration (FNA) images. We developed four deep learning models based on Vision Transformer (ViT) and... read more