AIMC Topic: Neural Networks, Computer

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Detecting Mandible Fractures in CBCT Scans Using a 3-Stage Neural Network.

Journal of dental research
After nasal bone fractures, fractures of the mandible are the most frequently encountered injuries of the facial skeleton. Accurate identification of fracture locations is critical for effectively managing these injuries. To address this need, JawFra...

The development of honey recognition models with broad applicability based on the association of isotope and elemental content with ANNs.

Food chemistry
Honey adulteration represents a worldwide problem, driven by the illicit economic gain that producers, traders, or merchants pursue. Among the falsification methods that can unfairly influence the price is the incorrect declaration of the botanical o...

Identifying radiogenomic associations of breast cancer based on DCE-MRI by using Siamese Neural Network with manufacturer bias normalization.

Medical physics
BACKGROUND AND PURPOSE: The immunohistochemical test (IHC) for Human Epidermal Growth Factor Receptor 2 (HER2) and hormone receptors (HR) provides prognostic information and guides treatment for patients with invasive breast cancer. The objective of ...

Integrative machine learning and neural networks for identifying PANoptosis-related lncRNA molecular subtypes and constructing a predictive model for head and neck squamous cell carcinoma.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: PANoptosis is considered a novel type of cell death that plays important roles in tumor progression. In this study, we applied machine learning algorithms to explore the relationships between PANoptosis-related lncRNAs (PRLs) and head and ne...

Advancing deep learning-based acoustic leak detection methods towards application for water distribution systems from a data-centric perspective.

Water research
Against the backdrop of severe leakage issue in water distribution systems (WDSs), numerous researchers have focused on the development of deep learning-based acoustic leak detection technologies. However, these studies often prioritize model develop...

Artificial neural networks for ECG interpretation in acute coronary syndrome: A scoping review.

The American journal of emergency medicine
INTRODUCTION: The electrocardiogram (ECG) is a crucial diagnostic tool in the Emergency Department (ED) for assessing patients with Acute Coronary Syndrome (ACS). Despite its widespread use, the ECG has limitations, including low sensitivity of the S...

Assessing gait dysfunction severity in Parkinson's Disease using 2-Stream Spatial-Temporal Neural Network.

Journal of biomedical informatics
Parkinson's Disease (PD), a neurodegenerative disorder, significantly impacts the quality of life for millions of people worldwide. PD primarily impacts dopaminergic neurons in the brain's substantia nigra, resulting in dopamine deficiency and gait i...

Advancing drug discovery with deep attention neural networks.

Drug discovery today
In the dynamic field of drug discovery, deep attention neural networks are revolutionizing our approach to complex data. This review explores the attention mechanism and its extended architectures, including graph attention networks (GATs), transform...

Topological Learning Approach to Characterizing Biological Membranes.

Journal of chemical information and modeling
Biological membranes play key roles in cellular compartmentalization, structure, and its signaling pathways. At varying temperatures, individual membrane lipids sample from different configurations, a process that frequently leads to higher-order pha...

Representations and generalization in artificial and brain neural networks.

Proceedings of the National Academy of Sciences of the United States of America
Humans and animals excel at generalizing from limited data, a capability yet to be fully replicated in artificial intelligence. This perspective investigates generalization in biological and artificial deep neural networks (DNNs), in both in-distribu...