AIMC Topic: Neural Networks, Computer

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Uncertainty-Aware Deep Learning and Structural Feature Analysis for Reliable Nephrotoxicity Prediction.

Journal of chemical information and modeling
Nephrotoxicity remains a critical safety concern in drug development and clinical practice. Despite their significance, existing computational models for nephrotoxicity prediction face challenges related to limited precision and reliability. To addre...

Efficient neural encoding as revealed by bilingualism.

Proceedings of the National Academy of Sciences of the United States of America
The remarkable human capacity for bilingual and multilingual acquisition raises fundamental questions about how the brain develops efficient systems for processing multiple languages. In this study, we used neural network models trained on natural sp...

Construction of a feature gene and machine prediction model for inflammatory bowel disease based on multichip joint analysis.

Journal of translational medicine
BACKGROUND: Inflammatory bowel disease (IBD) is a chronic nonspecific inflammatory disorder triggered by immune responses and genetic factors. Currently, there is no cure for IBD, and its etiology remains unclear. As a result, early detection and dia...

Multi-stage framework using transformer models, feature fusion and ensemble learning for enhancing eye disease classification.

Scientific reports
Eye diseases can affect vision and well-being, so early, accurate diagnosis is crucial to prevent serious impairment. Deep learning models have shown promise for automating the diagnosis of eye diseases from images. However, current methods mostly us...

Graph neural network-based drug-drug interaction prediction.

Scientific reports
With the growing variety of pharmacological compounds and the increasing need for polypharmacy, accurately predicting drug-drug interactions (DDIs) is essential to ensure both treatment efficacy and patient safety. Beneficial DDIs can enhance therape...

The role of personality traits in predicting educational use of generative AI in higher education.

Scientific reports
Generative Artificial Intelligence (Gen-AI) systems offer significant opportunities for personalized learning in higher education. Studying the effects of personality traits on the use of Gen-AI is crucial for understanding the role of individual dif...

Integrating advanced neural network architectures with privacy enhanced encryption for secure and intelligent healthcare analytics.

Scientific reports
Healthcare data protection in our mutually connected era has emerged as an issue of serious concern with private patient information, which has been exposed more often due to data violations and cyber-attacks. Network structures CNN and LSTM as part ...

Discovering action insights from large-scale assessment log data using machine learning.

Scientific reports
This study introduces a novel machine learning algorithm that combines natural language processing techniques, such as Word2Vec and Doc2Vec, with neural networks to identify and validate significant actions within human action sequences. Using the 20...

TrimNN: characterizing cellular community motifs for studying multicellular topological organization in complex tissues.

Nature communications
The spatial organization of cells plays a pivotal role in shaping tissue functions and phenotypes in various biological systems and diseased microenvironments. However, the topological principles governing interactions among cell types within spatial...

The chronODE framework for modelling multi-omic time series with ordinary differential equations and machine learning.

Nature communications
Many genome-wide studies capture isolated moments in cell differentiation or organismal development. Conversely, longitudinal studies provide a more direct way to study these kinetic processes. Here, we present an approach for modeling gene-expressio...