AI Medical Compendium

A Machine Learning-Enabled Method for Predicting the Tribological Performance of Materials Considering Surface/Interface Properties.

Langmuir : the ACS journal of surfaces and colloids Mar 22, 2026

The surface/interface properties of materials affect their tribological behavior significantly, necessitating quantitative research. Here, a hybrid machine learning model named CS-LSBoost (Cuckoo Searching-Least Square Boosting) is proposed to evalua... read more

Traffic crash data augmentation with multi-type variables using hybrid VAE-Diffusion generative neural networks for enhancing crash frequency modeling.

Accident; analysis and prevention Mar 22, 2026

Crash frequency modeling aims to analyze influential factors of crashes to enhance road safety. However, as crashes are inherently rare events, excessive zero observations in crash datasets undermine crash frequency models' ability to identify high-r... read more

Deep learning-based segmentation of aneurysmal subarachnoid hemorrhage: toward accurate and scalable prognostic imaging.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia Mar 22, 2026

BACKGROUND: Accurate segmentation of aneurysmal cerebral hemorrhages, including subarachnoid hemorrhage (SAH), intraparenchymal hemorrhage (IPH), and intraventricular hemorrhage (IVH), is essential for clinical decision-making. Manual segmentation, h... read more

Enhancing pulmonary embolism diagnosis: a squeeze-and-attention U-Net for precise detection and segmentation in CT angiography.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Mar 22, 2026

OBJECTIVE: Pulmonary embolism (PE) is a life-threatening condition requiring rapid and accurate diagnosis. This study proposes a deep learning-based approach for automated PE segmentation, focusing on both pixel-level accuracy and clinical applicabil... read more

Mechanical properties analysis of geopolymer concrete based on the sugarcane bagasse ash using machine learning.

Scientific reports Mar 22, 2026

Concussion pathophysiology: From biomechanical insult to clinical phenotype - or is injury truly the beginning?

Seminars in pediatric neurology Mar 22, 2026

Mild traumatic brain injury (mTBI) is associated with substantial morbidity worldwide. Emerging evidence demonstrates that both impact- and blast-related mTBI produce diffuse microstructural and functional alterations, e.g., diffuse axonal injury, as... read more

Generative binary memory: Pseudo-Replay class-Incremental learning on binarized embeddings.

Neural networks : the official journal of the International Neural Network Society Mar 21, 2026

In dynamic environments where new concepts continuously emerge, Deep Neural Networks (DNNs) must adapt by learning new classes while retaining previously acquired ones. This challenge is addressed by Class-Incremental Learning (CIL). This paper intro... read more

GCN combined with snake convolution for enhanced topological perception in thrombotic hepatic portal vein segmentation.

Medical image analysis Mar 21, 2026

The hemodynamic status of the portal vein plays a crucial role in the identification, treatment, and prognostic prediction of complications associated with liver cirrhosis. Accurate segmentation of the portal vein is essential for quantitative assess... read more

High diagnostic accuracy of a resnet50-based deep learning model for osteochondral lesions of the talus on magnetic resonance imaging.

Joint diseases and related surgery Mar 21, 2026

OBJECTIVES: This study aims to evaluate the diagnostic performance of a ResNet50-based convolutional neural network (CNN) in detecting osteochondral lesions of the talus (OLTs) on magnetic resonance imaging (MRI) and to compare its efficacy between T... read more

LLM-guided population-based reinforcement learning: A scalable methodology for adaptive hyperparameter optimization.

MethodsX Mar 21, 2026

Population-Based Training (PBT) has the drawback of using fixed, pre-programmed mutation and selection rules to optimize hyperparameters, which are not always flexible across reinforcement learning (RL) tasks. To address this, we introduce LLM-Guided... read more

Artificial Intelligence Medical Compendium