Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 42,831 to 42,840 of 223,853 articles

Do Commercial Airline Policies for Passengers With Obesity Carry Enough Weight?

Obesity science & practice Mar 11, 2026
INTRODUCTION: The travel industry has a responsibility to accommodate the needs of all its customers, including those with obesity. It is not known to what extent airlines communicate accessibility policies to passengers with obesity. We sought to as... read more 

Explainable machine learning to identify cannabinoid 1 receptor agonists.

Forensic science international Mar 11, 2026
Synthetic cannabinoid receptor agonists (SCRAs) are molecules that interact with the CB1 receptor and may exhibit greater psychoactive effect than CB1's natural agonists. Determining new SCRAs by conducting bioassays can be time-consuming and may or ... read more 

NeuroMix-DL: Improving imaging quality of a fast multiparametric MRI protocol using deep learning.

European journal of radiology Mar 11, 2026
PURPOSE: To improve the quality of a fast multi-contrast MR protocol acquisition using deep learning. MATERIALS AND METHODS: 350 patients (age: 64 ± 17 yrs; 155 male) underwent both a fast brain MR multi-contrast sequence (NeuroMix), capturing five c... read more 

Deep learning on histopathological images to predict breast cancer recurrence risk and chemotherapy benefit: a multicentre, model development and validation study.

The Lancet. Oncology Mar 11, 2026
BACKGROUND: Genomic assays such as Oncotype DX have transformed adjuvant treatment selection for hormone receptor-positive, HER2-negative, early breast cancer but remain inaccessible to many patients because of high cost and logistical barriers. We a... read more 

Preliminary assessment of AI as a triage tool for forensic toxicology case interpretation.

Forensic science international Mar 11, 2026
Large language models (LLMs) such as ChatGPT have demonstrated potential for interpretation in various scientific disciplines; however, their application in forensic toxicology remains unexamined. We wanted to investigate the performance of LLMs comp... read more 

Considerations for enhancing the clinical translational potential of LLM-Based TBI mortality prediction models.

International journal of medical informatics Mar 11, 2026
This study explores the use of GPT-5 and traditional machine learning by scholars such as Tu et al. to predict the risk of emergency death in traumatic brain injury (TBI), and affirms the value of their experimental design and method exploration in p... read more 

Recurrent spiking neural networks with bimodal neuronal time scales for learning performance enhancement.

Neural networks : the official journal of the International Neural Network Society Mar 11, 2026
Recurrent Spiking Neural Networks (RSNNs) represent a crucial paradigm in neuromorphic computing, with their performance heavily dependent on the design of neuronal time scales. Neuroscientific research has established that biological cortical circui... read more 

Geometric perspectives on multi-input reservoir computing.

Neural networks : the official journal of the International Neural Network Society Mar 11, 2026
A geometric framework for multi-input reservoir computing is developed. Channel-wise Gramians, principal angles, and a coupling index are used to characterise collapse, decoupling, and a nontrivial multimodal regime within a single recurrent system. ... read more 

Deep learning algorithms for license plate recognition: A review.

Neural networks : the official journal of the International Neural Network Society Mar 11, 2026
License plate recognition serves as a crucial link in the intelligent transportation system and vehicle management. It lies at the heart of enhancing road supervision efficiency and enabling automated services. However, the rapid advancement in this ... read more 

SCADA: Sparse cross attention for domain adaptive semantic segmentation.

Neural networks : the official journal of the International Neural Network Society Mar 11, 2026
Unsupervised domain adaptive (UDA) semantic segmentation intends to perform satisfactory dense prediction on unannotated target (real-world) images by leveraging a learned model trained on annotated source (synthetic) images. Although many models hav... read more 
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