Neural networks : the official journal of the International Neural Network Society
Dec 30, 2024
To tackle high communication costs and privacy issues in Centralized Federated Learning (CFL), Decentralized Federated Learning (DFL) is an alternative. However, a significant discrepancy exists between local updates and the expected global update, k...
Computer methods and programs in biomedicine
Dec 30, 2024
BACKGROUND: Gastrointestinal (GI) diseases pose significant challenges for healthcare systems, largely due to the complexities involved in their detection and treatment. Despite the advancements in deep neural networks, their high computational deman...
Food research international (Ottawa, Ont.)
Dec 30, 2024
The detection of adulteration in apple juice concentrate is critical for ensuring product authenticity and consumer safety. This study evaluates the effectiveness of artificial neural networks (ANN) and support vector machines (SVM) in analyzing spec...
Food research international (Ottawa, Ont.)
Dec 30, 2024
Diverse species of yeasts are commonly associated with food and food production environments. The contamination of food products by spoilage yeasts poses significant challenges, leading to quality degradation and food loss. Similarly, the introductio...
5-Methylcytosine (m5C) plays a pivotal role in various RNA metabolic processes, including RNA localization, stability, and translation. Current high-throughput sequencing technologies for m5C site identification are resource-intensive in terms of cos...
Journal of chemical information and modeling
Dec 30, 2024
Machine learning (ML) models now play a crucial role in predicting properties essential to drug development, such as a drug's logscale acid-dissociation constant (p). Despite recent architectural advances, these models often generalize poorly to nove...
Journal of chemical information and modeling
Dec 30, 2024
Machine learning methods for fitting potential energy surfaces and molecular dynamics simulations are becoming increasingly popular due to their potentially high accuracy and savings in computational resources. However, existing application models of...
Early detection of autism spectrum disorder (ASD) is particularly important given its insidious qualities and the high cost of the diagnostic process. Currently, static functional connectivity studies have achieved significant results in the field of...
Chronic kidney disease (CKD) imposes a high burden with high mortality and morbidity rates. Early detection of CKD is imperative in preventing the adverse outcomes attributed to the later stages. Therefore, this study aims to utilize machine learning...
Multiple sclerosis (MS) is a severe brain disease that permanently destroys brain cells, impacting vision, balance, muscle control, and daily activity. This research employs a weighted combination of deep neural networks and optimization techniques f...
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