AIMC Topic: Algorithms

Clear Filters Showing 24521 to 24530 of 28713 articles

Use of a Dual Artificial Intelligence Platform to Detect Unreported Lung Nodules.

Journal of computer assisted tomography
OBJECTIVE: To investigate the performance of Dual-AI Deep Learning Platform in detecting unreported pulmonary nodules that are 6 mm or greater, comprising computer-vision (CV) algorithm to detect pulmonary nodules, with positive results filtered by n...

Data Interpretation in Structural Health Monitoring: Toward a Universal Language.

Sensors (Basel, Switzerland)
Structural Health Monitoring (SHM) relies on the effective communication between sensors and diagnostic systems, yet data interpretation remains inconsistent and subjective. This paper introduces a novel perspective, viewing data as a form of languag...

YOLO-TARC: YOLOv10 with Token Attention and Residual Convolution for Small Void Detection in Root Canal X-Ray Images.

Sensors (Basel, Switzerland)
The detection of small voids or defects in X-ray images of tooth root canals still faces challenges. To address the issue, this paper proposes an improved YOLOv10 that combines Token Attention with Residual Convolution (ResConv), termed YOLO-TARC. To...

A novel approach to cancer treatment planning using inverse sum indeg index of fuzzy graphs.

Scientific reports
Fuzzy graph theory, with its ability to handle uncertainty and varying relationship strengths, offers a powerful tool for modeling and solving complex problems across diverse fields like medical, social network, biological networks, etc. The topologi...

Application of interpretable machine learning algorithms to predict macroangiopathy risk in Chinese patients with type 2 diabetes mellitus.

Scientific reports
Macrovascular complications are leading causes of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM), yet early diagnosis of cardiovascular disease (CVD) in this population remains clinically challenging. This study aims to deve...

Classification of multi-lead ECG based on multiple scales and hierarchical feature convolutional neural networks.

Scientific reports
Detecting and classifying arrhythmias is essential in diagnosing cardiovascular diseases. However, current deep learning-based classification methods often encounter difficulties in effectively integrating both the morphological and temporal features...

Enhancing noninvasive pancreatic cystic neoplasm diagnosis with multimodal machine learning.

Scientific reports
Pancreatic cystic neoplasms (PCNs) are a complex group of lesions with a spectrum of malignancy. Accurate differentiation of PCN types is crucial for patient management, as misdiagnosis can result in unnecessary surgeries or treatment delays, affecti...

Automated seizure detection in epilepsy using a novel dynamic temporal-spatial graph attention network.

Scientific reports
Epilepsy is a neurological disorder characterized by recurrent seizures caused by excessive electrical discharges in brain cells, posing significant diagnostic and therapeutic challenges. Dynamic brain network analysis via electroencephalography (EEG...

Application of improved graph convolutional network for cortical surface parcellation.

Scientific reports
Accurate cortical surface parcellation is essential for elucidating brain organizational principles, functional mechanisms, and the neural substrates underlying higher cognitive and emotional processes. However, the cortical surface is a highly folde...

Predictive machine learning algorithm for COPD exacerbations using a digital inhaler with integrated sensors.

BMJ open respiratory research
PURPOSE: By using data obtained with digital inhalers, machine learning models have the potential to detect early signs of deterioration and predict impending exacerbations of chronic obstructive pulmonary disease (COPD) for individual patients. This...