AIMC Topic: Algorithms

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AI-driven glomerular morphology quantification: a novel pipeline for assessing basement membrane thickness and podocyte foot process effacement in kidney diseases.

Computer methods and programs in biomedicine May 7, 2025
BACKGROUND AND OBJECTIVE: Measuring the thickness of the glomerular basement membrane (GBM) and assessing the percentage of podocyte foot process effacement (%PFPE) are important for diagnosing non-neoplastic kidney diseases. However, when performed ...
Deep Learning Image Processing, Computer-Assisted Kidney Diseases Humans Algorithms Microscopy, Electron Podocytes Glomerular Basement Membrane Biopsy Kidney Glomerulus
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Learning Emotion Category Representation to Detect Emotion Relations Across Languages.

IEEE transactions on pattern analysis and machine intelligence May 7, 2025
Understanding human emotions is crucial for a myriad of applications, from psychological research to advancements in Natural Language Processing (NLP). Traditionally, emotions are categorized into distinct basic groups, which has led to the developme...
Emotions Machine Learning Humans Algorithms Natural Language Processing Neural Networks, Computer Language
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Sculpting molecules in text-3D space: a flexible substructure aware framework for text-oriented molecular optimization.

BMC bioinformatics May 7, 2025
The integration of deep learning, particularly AI-Generated Content, with high-quality data derived from ab initio calculations has emerged as a promising avenue for transforming the landscape of scientific research. However, the challenge of designi...
Algorithms Drug Design Molecular Structure Deep Learning
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An innovative machine learning approach for slope stability prediction by combining shap interpretability and stacking ensemble learning.

Environmental science and pollution research international May 7, 2025
Accurate slope stability prediction is crucial for mitigating slope failures, but conventional methods are challenging due to their complexity and high data requirements. To overcome these limitations, researchers have used machine learning (ML) tech...
Algorithms Machine Learning Ensemble Learning
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Synthetic Lung Ultrasound Data Generation Using Autoencoder With Generative Adversarial Network.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control May 7, 2025
Class imbalance is a significant challenge in medical image analysis, particularly in lung ultrasound (LUS), where severe patterns are often underrepresented. Traditional oversampling techniques, which simply duplicate original data, have limited eff...
Humans Autoencoder Lung Neural Networks, Computer Generative Adversarial Networks Ultrasonography Algorithms Image Processing, Computer-Assisted
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Unsupervised Test-Time Adaptation for Hepatic Steatosis Grading Using Ultrasound B-Mode Images.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control May 7, 2025
Ultrasound (US) is considered a key modality for the clinical assessment of hepatic steatosis (i.e., fatty liver) due to its noninvasiveness and availability. Deep learning methods have attracted considerable interest in this field, as they are capab...
Ultrasonography Fatty Liver Unsupervised Machine Learning Image Interpretation, Computer-Assisted Liver Middle Aged Deep Learning Female Male Neural Networks, Computer Algorithms Humans
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BentRay-NeRF: Bent-Ray Neural Radiance Fields for Robust Speed-of-Sound Imaging in Ultrasound Computed Tomography.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control May 7, 2025
Ultrasound computed tomography (USCT) is a promising technique for breast cancer detection because of its quantitative imaging capability of the speed of sound (SOS) of soft tissues and the fact that malignant breast lesions often have a higher SOS c...
Algorithms Tomography, X-Ray Computed Female Humans Neural Networks, Computer Image Processing, Computer-Assisted Breast Phantoms, Imaging Breast Neoplasms Ultrasonography
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A KAN-based hybrid deep neural networks for accurate identification of transcription factor binding sites.

PloS one May 7, 2025
BACKGROUND: Predicting protein-DNA binding sites in vivo is a challenging but urgent task in many fields such as drug design and development. Most promoters contain many transcription factor (TF) binding sites, yet only a few have been identified thr...
Protein Binding Computational Biology Promoter Regions, Genetic Algorithms Binding Sites Transcription Factors Deep Learning Humans Neural Networks, Computer
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Forecasting second-hand house prices in China using the GA-PSO-BP neural network model.

PloS one May 7, 2025
While the traditional genetic algorithms are capable of forecasting house prices, they often suffer from premature convergence, which adversely affects the reliability of the forecasts. To address this issue, the research employs a genetic-particle s...
Algorithms Forecasting China Humans Housing Models, Economic Neural Networks, Computer Commerce
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Identification of medicinal plant parts using depth-wise separable convolutional neural network.

PloS one May 7, 2025
Identifying relevant plant parts is one of the most significant tasks in the pharmaceutical industry. Correct identification minimizes the risk of mis-identification, which might have unfavorable effects, and it ensures that plants are used medicinal...
Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Deep Learning Plant Leaves Convolutional Neural Networks Plants, Medicinal
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