AIMC Topic: Neural Networks, Computer

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Detection of Negative Emotions in Short Texts Using Deep Neural Networks.

Cyberpsychology, behavior and social networking May 7, 2025
Emotion detection is crucial in various domains, including psychology, health, social sciences, and marketing. Specifically, in psychology, identifying negative emotions in short Spanish texts, such as tweets, is vital for understanding individuals' ...
Emotions Social Media Spain Humans Neural Networks, Computer Deep Learning
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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...
Language Emotions Natural Language Processing Machine Learning Algorithms Humans Neural Networks, Computer
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A deep learning model combining circulating tumor cells and radiological features in the multi-classification of mediastinal lesions in comparison with thoracic surgeons: a large-scale retrospective study.

BMC medicine May 7, 2025
BACKGROUND: CT images and circulating tumor cells (CTCs) are indispensable for diagnosing the mediastinal lesions by providing radiological and intra-tumoral information. This study aimed to develop and validate a deep multimodal fusion network (DMFN...
Female Mediastinal Neoplasms Humans Aged Neural Networks, Computer Adult Deep Learning Male Retrospective Studies Neoplastic Cells, Circulating Surgeons Tomography, X-Ray Computed Thoracic Surgery Middle Aged
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Event driven neural network on a mixed signal neuromorphic processor for EEG based epileptic seizure detection.

Scientific reports May 7, 2025
Long-term monitoring of biomedical signals is essential for the modern clinical management of neurological conditions such as epilepsy. However, developing wearable systems that are able to monitor, analyze, and detect epileptic seizures with long-la...
Seizures Signal Processing, Computer-Assisted Neural Networks, Computer Electroencephalography Humans Epilepsy
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EEG-based neurodegenerative disease diagnosis: comparative analysis of conventional methods and deep learning models.

Scientific reports May 7, 2025
In the context of lifestyle changes, stress and other environmental factors have resulted in the sudden hike in dementia globally. This necessitates investigations with respect to every horizon of the due cause for it; further on, the diagnosis and t...
Humans Neural Networks, Computer Deep Learning Cognitive Dysfunction Alzheimer Disease Electroencephalography Frontotemporal Dementia Neurodegenerative Diseases
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Predictive biophysical neural network modeling of a compendium of in vivo transcription factor DNA binding profiles for Escherichia coli.

Nature communications May 7, 2025
The DNA binding of most Escherichia coli Transcription Factors (TFs) has not been comprehensively mapped, and few have models that can quantitatively predict binding affinity. We report the global mapping of in vivo DNA binding for 139 E. coli TFs us...
Chromatin Immunoprecipitation Sequencing Protein Binding DNA, Bacterial Transcription Factors Escherichia coli Escherichia coli Proteins Binding Sites Neural Networks, Computer
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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...
Ultrasonography Image Processing, Computer-Assisted Autoencoder Generative Adversarial Networks Neural Networks, Computer Algorithms Lung Humans
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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...
Male Middle Aged Deep Learning Algorithms Female Unsupervised Machine Learning Image Interpretation, Computer-Assisted Ultrasonography Fatty Liver Liver Humans Neural Networks, Computer
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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...
Humans Ultrasonography Image Processing, Computer-Assisted Tomography, X-Ray Computed Breast Female Neural Networks, Computer Breast Neoplasms Phantoms, Imaging Algorithms
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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...
Computational Biology Algorithms Binding Sites Transcription Factors Deep Learning Humans Promoter Regions, Genetic Protein Binding Neural Networks, Computer
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