AIMC Topic: Neural Networks, Computer

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Automated Classification of Sleep-Wake States and Seizures in Mice.

eNeuro
Sleep-wake states bidirectionally interact with epilepsy and seizures, but the mechanisms are unknown. A barrier to comprehensive characterization and the study of mechanisms has been the difficulty of annotating large chronic recording datasets. To ...

Enhanced local feature extraction of lite network with scale-invariant CNN for precise segmentation of small brain tumors in MRI.

PloS one
Deep learning has emerged as the preeminent technique for semantic segmentation of brain MRI tumors. However, existing methods often rely on hierarchical downsampling to generate multi-scale feature maps, effectively capturing fine-grained global fea...

Fault detection of high-speed train wheelset bearings based on improved auxiliary classifier generative adversarial networks and VAE.

PloS one
Fault detection in high-speed train wheelset bearings is paramount for ensuring operational safety. However, the scarcity of fault samples limits the accuracy of traditional detection methods. To address this challenge, this paper proposes a supervis...

Credit risk prediction model for listed companies based on improved reinforcement learning and Bayesian optimization hyperband.

PloS one
The financial sector has experienced swift growth over recent years, leading to the escalating prominence of credit risk among publicly traded companies. Consequently, forecasting credit risk for these firms has emerged as a critical task for banks, ...

A multitask modelling framework for tablet manufacturability and quality attributes in direct compression using knowledge-guided neural networks.

International journal of pharmaceutics
Assessing the feasibility of a manufacturing route for a given formulation and process is a key initial step in drug product development. Additionally, the final product must meet a series of critical quality attributes to be considered suitable to m...

Predicting COVID-19 patient recovery or mortality using deep neural decision tree and forest.

BMC research notes
OBJECTIVE: Identifying patients at high risk of mortality is crucial for emergency physicians to allocate hospital resources effectively, particularly in regions with limited medical services. This need becomes even more pressing during global health...

Adaptive identity-regularized generative adversarial networks with species-specific loss functions for enhanced fish classification and segmentation through data augmentation.

Scientific reports
Traditional fish classification systems suffer from limited training data and imbalanced datasets, particularly for rare or morphologically complex species. This paper presents a novel Generative Adversarial Network architecture that integrates adapt...

Enhancing the precision of male fertility diagnostics through bio inspired optimization techniques.

Scientific reports
Infertility is a growing concern in today's technologically driven and mechanized world, with male related factors contributing to nearly half of all cases yet often remaining under diagnosed due to societal misconceptions and stigma. Prolonged seden...

Inter-machine harmonization of multicenter echocardiographic images for improvement of left ventricular ejection fraction prediction model.

Scientific reports
One of the common challenges in medical artificial intelligence (AI) applications using echocardiography is the lack of image data harmonization. This study aims to improve the prediction accuracy of left ventricular ejection fraction (LVEF) AI model...

A neural architecture search optimized lightweight attention ensemble model for nutrient deficiency and severity assessment in diverse crop leaves.

Scientific reports
The growth and productivity of banana crops are critically affected by micronutrient deficiencies, which are often difficult to detect at early stages. Lightweight deep learning models, optimized through neural architecture search (NAS) and attention...