AIMC Topic: Autoencoder

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scVAEDer: integrating deep diffusion models and variational autoencoders for single-cell transcriptomics analysis.

Genome biology Mar 21, 2025
Discovering a lower-dimensional embedding of single-cell data can improve downstream analysis. The embedding should encapsulate both the high-level features and low-level variations. While existing generative models attempt to learn such low-dimensio...
Single-Cell Analysis Autoencoder Deep Learning Software Gene Expression Profiling Transcriptome Humans
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Enhancing parkinson disease detection through feature based deep learning with autoencoders and neural networks.

Scientific reports Mar 13, 2025
Parkinson's disease is a neurodegenerative disorder that is associated with aging, leading to the progressive deterioration of certain regions of the brain. Accurate and timely diagnosis plays a crucial role in facilitating optimal therapy and improv...
Humans Aged Male Middle Aged Neural Networks, Computer Female Autoencoder Deep Learning Parkinson Disease
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NaMA-Mamba: Foundation model for generalizable nasal disease detection using masked autoencoder with Mamba on endoscopic images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Mar 12, 2025
Artificial intelligence (AI) has shown great promise in analyzing nasal endoscopic images for disease detection. However, current AI systems require extensive expert-labeled data for each specific medical condition, limiting their applications. In th...
Autoencoder Nose Diseases Endoscopy Image Interpretation, Computer-Assisted Humans Machine Learning Algorithms Artificial Intelligence
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Multi-Omics Deep-Learning Prediction of Homologous Recombination Deficiency-Like Phenotype Improved Risk Stratification and Guided Therapeutic Decisions in Gynecological Cancers.

IEEE journal of biomedical and health informatics Mar 6, 2025
Homologous recombination deficiency (HRD) is a well-recognized important biomarker in determining the clinical benefits of platinum-based chemotherapy and PARP inhibitor therapy for patients diagnosed with gynecologic cancers. Accurate prediction of ...
Biomarkers, Tumor Risk Assessment Genomics Phenotype Female Genital Neoplasms, Female Autoencoder Homologous Recombination Humans DNA Methylation Multiomics Ovarian Neoplasms
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Near-lossless EEG signal compression using a convolutional autoencoder: Case study for 256-channel binocular rivalry dataset.

Computers in biology and medicine Mar 5, 2025
Electroencephalography (EEG) experiments typically generate vast amounts of data due to the high sampling rates and the use of multiple electrodes to capture brain activity. Consequently, storing and transmitting these large datasets is challenging, ...
Electroencephalography Signal Processing, Computer-Assisted Humans Autoencoder Neural Networks, Computer Data Compression
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AD-VAE: Adversarial Disentangling Variational Autoencoder.

Sensors (Basel, Switzerland) Mar 4, 2025
Face recognition (FR) is a less intrusive biometrics technology with various applications, such as security, surveillance, and access control systems. FR remains challenging, especially when there is only a single image per person as a gallery datase...
Autoencoder Automated Facial Recognition Face Biometric Identification Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Algorithms Humans
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Improving explanations for medical X-ray diagnosis combining variational autoencoders and adversarial machine learning.

Computers in biology and medicine Feb 24, 2025
Explainability in Medical Computer Vision is one of the most sensible implementations of Artificial Intelligence nowadays in healthcare. In this work, we propose a novel Deep Learning architecture for eXplainable Artificial Intelligence, specially de...
Autoencoder Algorithms Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Machine Learning Humans
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Sensory-biased autoencoder enables prediction of texture perception from food rheology.

Food research international (Ottawa, Ont.) Feb 15, 2025
Understanding how the physical properties of food affect sensory perception remains a critical challenge for food design. Here, we present an innovative machine learning strategy to decode the complex relationships between non-Newtonian rheological a...
Autoencoder Adult Humans Machine Learning Female Rheology Neural Networks, Computer Male Young Adult Taste Food
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Circular RNA-Drug Association Prediction Based on Multi-Scale Convolutional Neural Networks and Adversarial Autoencoders.

International journal of molecular sciences Feb 11, 2025
The prediction of circular RNA (circRNA)-drug associations plays a crucial role in understanding disease mechanisms and identifying potential therapeutic targets. Traditional methods often struggle to cope with the complexity of heterogeneous network...
Neural Networks, Computer Autoencoder Algorithms Humans RNA, Circular Computational Biology Convolutional Neural Networks Pharmaceutical Preparations
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Generative and contrastive graph representation learning with message passing.

Neural networks : the official journal of the International Neural Network Society Feb 6, 2025
Self-supervised graph representation learning (SSGRL) has emerged as a promising approach for graph embeddings because it does not rely on manual labels. SSGRL methods are generally divided into generative and contrastive approaches. Generative metho...
Generative Artificial Intelligence Graph Neural Networks Supervised Machine Learning Datasets as Topic Autoencoder
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