AIMC Topic: Algorithms

Clear Filters Showing 861 to 870 of 28713 articles

CXR-MultiTaskNet a unified deep learning framework for joint disease localization and classification in chest radiographs.

Scientific reports
Chest X-ray (CXR) is a challenging problem in automated medical diagnosis, where complex visual patterns of thoracic diseases must be precisely identified through multi-label classification and lesion localization. Current approaches typically consid...

Edge computing with federated learning for early detection of citric acid overdose and adjustment of regional citrate anticoagulation.

BMC medical informatics and decision making
Regional citrate anticoagulation (RCA) is critical for extracorporeal anticoagulation in continuous renal replacement therapy done at the bedside. To make patients' data more secure and to help with computer-based monitoring of dosages, we suggest a ...

Segmentation-enhanced approach for emotion detection from EEG signals using the fuzzy C-mean and SVM.

Scientific reports
The analysis of EEG signals for determining emotion is one of the most important topics in the field of artificial intelligence. It can be applied in a wide variety of areas, such as emotional health care and the man/machine interface. The purpose of...

Semi-supervised GAN with hybrid regularization and evolutionary hyperparameter tuning for accurate melanoma detection.

Scientific reports
Melanoma, influenced by changes in deoxyribonucleic acid (DNA), requires early detection for effective treatment. Traditional melanoma research often employs supervised learning methods, which necessitate large, labeled datasets and are sensitive to ...

A model for epileptic EEG detection and recognition based on Multi-Attention mechanism and Spatiotemporal.

Scientific reports
In the field of neuroscience, epilepsy is a chronic non-communicable brain disease that affects approximately 50 million people worldwide. Electroencephalography (EEG) has become a key tool in detecting and characterizing human neurological diseases ...

Current state and open problems in universal differential equations for systems biology.

NPJ systems biology and applications
Universal Differential Equations (UDEs) combine mechanistic differential equations with data-driven artificial neural networks, forming a flexible framework for modelling complex biological systems. This hybrid approach leverages prior knowledge and ...

Graph Learning-Based Scoring of RNA-Protein Complex Structures.

Journal of chemical theory and computation
Development of suitable scoring functions is essential for the prediction of RNA-protein complex structures. Conventional statistical potential-based scoring functions suffered from deficiencies in handling conformational flexibility. The recent appl...

Assessment of university students' earthquake coping strategies using artificial intelligence methods.

Scientific reports
Earthquakes are one of the most destructive natural disasters that pose a serious threat to human life and infrastructure worldwide. The aim of this study is to evaluate the coping strategies of adult individuals in Turkey regarding earthquake stress...

Multimodal feature distinguishing and deep learning approach to detect lung disease from MRI images.

Scientific reports
Precise and early detection and diagnosis of lung diseases reduce the severity of life risk and further spread of infections in patients. Computer-based image processing techniques utilize magnetic resonance imaging (MRI) as input for computing, dete...

Deep Learning Radiomics Model Based on Computed Tomography Image for Predicting the Classification of Osteoporotic Vertebral Fractures: Algorithm Development and Validation.

JMIR medical informatics
BACKGROUND: Osteoporotic vertebral fractures (OVFs) are common in older adults and often lead to disability if not properly diagnosed and classified. With the increased use of computed tomography (CT) imaging and the development of radiomics and deep...