AIMC Topic: Neural Networks, Computer
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Latent space autoencoder generative adversarial model for retinal image synthesis and vessel segmentation.
BMC medical imaging
May 5, 2025
Diabetes is a widespread condition that can lead to serious vision problems over time. Timely identification and treatment of diabetic retinopathy (DR) depend on accurately segmenting retinal vessels, which can be achieved through the invasive techni...
Optimizing non small cell lung cancer detection with convolutional neural networks and differential augmentation.
Scientific reports
May 5, 2025
Lung cancer remains one of the leading causes of cancer-related deaths worldwide, with early detection being critical to improving patient outcomes. Recent advancements in deep learning have shown promise in enhancing diagnostic accuracy, particularl...
Integrating SAM priors with U-Net for enhanced multiclass cell detection in digital pathology.
Scientific reports
May 5, 2025
In digital pathology, the accurate detection, segmentation, and classification of cells are pivotal for precise pathological diagnosis. Traditionally, pathologists manually segment cells from pathological images to facilitate diagnosis based on these...
Dense dynamic convolutional network for Bel canto vocal technique assessment.
Scientific reports
May 5, 2025
The Bel Canto performance is a complex and multidimensional art form encompassing pitch, timbre, technique, and affective expression. To accurately reflect a performer's singing proficiency, it is essential to quantify and evaluate their vocal techni...
An efficient patient's response predicting system using multi-scale dilated ensemble network framework with optimization strategy.
Scientific reports
May 5, 2025
The forecasting of a patient's response to radiotherapy and the likelihood of experiencing harmful long-term health impacts would considerably enhance individual treatment plans. Due to the continuous exposure to radiation, cardiovascular disease and...
An attention based hybrid approach using CNN and BiLSTM for improved skin lesion classification.
Scientific reports
May 5, 2025
Skin lesions remain a significant global health issue, with their incidence rising steadily over the past few years. Early and accurate detection is crucial for effective treatment and improving patient outcomes. This work explores the integration of...
Enhancing Cardiopulmonary Resuscitation Quality Using a Smartwatch: Neural Network Approach for Algorithm Development and Validation.
JMIR mHealth and uHealth
May 5, 2025
BACKGROUND: Sudden cardiac arrest is a major cause of mortality, necessitating immediate and high-quality cardiopulmonary resuscitation (CPR) for improved survival rates. High-quality CPR is defined by chest compressions at a rate of 100-120 per minu...
TCN-QV: an attention-based deep learning method for long sequence time-series forecasting of gold prices.
PloS one
May 5, 2025
Accurate prediction of gold prices is crucial for investment decision-making and national risk management. The time series data of gold prices exhibits random fluctuations, non-linear characteristics, and high volatility, making prediction extremely ...
Improving fine-grained food classification using deep residual learning and selective state space models.
PloS one
May 5, 2025
BACKGROUND: Food classification is the foundation for developing food vision tasks and plays a key role in the burgeoning field of computational nutrition. Due to the complexity of food requiring fine-grained classification, the Convolutional Neural ...
Classification of Neuropsychiatric Disorders via Brain-Region-Selected Graph Convolutional Network.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 5, 2025
For the classification of patients with neuropsychiatric disorders based on rs-fMRI data, this paper proposed a Brain-Region-Selected graph convolutional network (BRS-GCN). In order to effectively identify the most significant biomarkers associated w...
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