Search Results - Relevance factor variational autoencoder*

Developing a fair and interpretable representation of the clock drawing test for mitigating low education and racial bias

Authors: Jiaqing Zhang Sabyasachi Bandyopadhyay Faith Kimmet et al.

Source: Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)

Subject Terms: AI Fairness, Semi-supervised deep learning, Relevance factor variational autoencoder, Mini-mental state examination, Attention, Memory, Medicine, Science

File Description: electronic resource

Relation: https://doaj.org/toc/2045-2322

Access URL: https://doaj.org/article/debc7f1b53414c13b7951f793386fe4a

Combining variational autoencoders with generative adversarial networks to adaptively adjust the electromagnetic compatibility of biomechanical data analysis platforms.

Authors: Sun, Hongyan Zhu, Mingxiang Wang, Xingbo

Source: Molecular & Cellular Biomechanics; 2025, Vol. 22 Issue 5, p1-17, 17p

Subject Terms: ELECTROMAGNETIC compatibility, GENERATIVE adversarial networks, PROBABILISTIC generative models, DATA augmentation, BIOMECHANICS, WEARABLE technology, ELECTROMAGNETIC interference

Exploring the Potential of Variational Autoencoders for Modeling Nonlinear Relationships in Psychological Data.

Authors: Milano, Nicola Casella, Monica Esposito, Raffaella et al.

Source: Behavioral Sciences (2076-328X); Jul2024, Vol. 14 Issue 7, p527, 23p

VGAE-Hub: a variational graph autoencoder framework for identifying shared hub genes in colorectal cancer and inflammatory bowel disease.

Authors: Joshi, Pratibha Verma, Ravi Singh, Buddha

Source: Network Modeling & Analysis in Health Informatics & Bioinformatics; 11/4/2025, Vol. 14 Issue 1, p1-18, 18p

Survey on sampling conditioned brain images and imaging measures with generative models.

Authors: Cheong, Sehyoung Lee, Hoseok Kim, Won Hwa

Source: Biomedical Engineering Letters; Sep2025, Vol. 15 Issue 5, p831-843, 13p

A vision transformer approach for fully automated and scalable dementia screening using clock drawing test images.

Authors: Bone, Michael B. Freedman, Morris Black, Sandra E. et al.

Source: Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring; Jul-Sep2025, Vol. 17 Issue 3, p1-10, 10p

Subject Terms: DEMENTIA, IMAGE analysis, MEDICAL screening, DIAGNOSTIC services, DEEP learning, COGNITIVE testing, TRANSFORMER models

Loop closure detection of visual SLAM based on variational autoencoder.

Authors: Shibin Song Fengjie Yu Xiaojie Jiang et al.

Source: Frontiers in Neurorobotics; 2024, p1-13, 13p

Subject Terms: DEEP learning, IMAGE representation, HANDICRAFT

An Effective Fusion and Deeplift-based Optimized Hamiltonian Relevance Aware Capsule Network for Glitch Classification in LIGO.

Authors: Agrawal, Surbhi

Source: Cognitive Computation; Dec2025, Vol. 17 Issue 6, p1-20, 20p

A Systematic Review of User Attitudes Toward GenAI: Influencing Factors and Industry Perspectives.

Authors: Chen, Junjie Xie, Wei Xie, Qing et al.

Source: Journal of Intelligence; Jul2025, Vol. 13 Issue 7, p78, 46p

Subject Terms: GENERATIVE artificial intelligence, HUMAN-artificial intelligence interaction, ATTITUDE (Psychology), CROSS-cultural studies, SUSTAINABLE development, ARTIFICIAL intelligence, CREATIVE ability, TECHNOLOGY Acceptance Model

Signed versus isomorphic graph autoencoders for microRNA-single-nucleotide polymorphisms network reconstruction in periodontal osteo-genomic landscapes.

Alternate Title: Autocodificadores de grafos isomorfos versus firmados para la reconstrucción de redes de polimorfismos de un solo nucleótido de microARN en paisajes osteogenómicos periodontales. (Spanish)

Authors: Sharma, Sarvagya Yadalam, Pradeep Kumar Ardila, Carlos M.

Source: Gaceta Médica de Caracas; jul-sep2025, Vol. 133 Issue 3, p675-685, 11p

Artificial Intelligence in Endurance Sports: Metabolic, Recovery, and Nutritional Perspectives.

Authors: Grivas, Gerasimos V. Safari, Kousar

Source: Nutrients. Oct2025, Vol. 17 Issue 20, p3209. 26p.

Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly Detection

Authors: Challu, Cristian Jiang, Peihong Wu, Ying Nian et al.

Index Terms: Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2202.07586

AACNet: attention aided CNN-autoencoder network for precise categorization of respiratory conditions from HRCT scans.

Authors: Kakati, Anchita Bhattacharjya, Upasana Medhi, Jyoti Prakash et al.

Source: Network Modeling & Analysis in Health Informatics & Bioinformatics; 8/20/2025, Vol. 14 Issue 1, p1-29, 29p

Explainable semi-supervised deep learning shows that dementia is associated with small, avocado-shaped clocks with irregularly placed hands.

Authors: Bandyopadhyay, Sabyasachi Wittmayer, Jack Libon, David J. et al.

Source: Scientific Reports; 5/6/2023, Vol. 13 Issue 1, p1-12, 12p

Subject Terms: SUPERVISED learning, CLOCKS & watches, DEEP learning, AVOCADO, DEMENTIA, RECEIVER operating characteristic curves, CIRCADIAN rhythms

Beyond Relevance: Factor-level Causal Explanation for User Travel Decisions with Counterfactual Data Augmentation.

Authors: Li, Hanzhe Gu, Jingjing Lu, Xinjiang et al.

Source: ACM Transactions on Information Systems; Sep2024, Vol. 42 Issue 5, p1-31, 31p

Sparse Regularized Autoencoders-Based Radiomics Data Augmentation for Improved EGFR Mutation Prediction in NSCLC.

Authors: Munir, Muhammad Asif Shah, Reehan Ali Waheed, Urooj et al.

Source: Future Internet; Nov2025, Vol. 17 Issue 11, p495, 23p

Subject Terms: LUNG cancer, EPIDERMAL growth factor receptors, RADIOMICS, AUTOENCODERS, MACHINE learning, ONCOLOGY, DATA augmentation

EEG-Based ADHD Classification Using Autoencoder Feature Extraction and ResNet with Double Augmented Attention Mechanism.

Authors: Bansal, Jayoti Gangwar, Gaurav Aljaidi, Mohammad et al.

Source: Brain Sciences (2076-3425); Jan2025, Vol. 15 Issue 1, p95, 22p

Subject Terms: CHILD patients, FEATURE selection, DEEP learning, AUTOENCODERS, FEATURE extraction

Synergizing Attribute-Guided Latent Space Exploration (AGLSE) with Classical Molecular Simulations to Design Potent Pep-Magnet Peptide Inhibitors to Abrogate SARS-CoV-2 Host Cell Entry.

Authors: Ullah, Farhan Xiao, Aobo Ullah, Shahid et al.

Source: Viruses (1999-4915); Jun2025, Vol. 17 Issue 6, p828, 25p

Subject Terms: SARS-CoV-2, SARS-CoV-2 Omicron variant, MACHINE learning, COVID-19, MOLECULAR dynamics, DEEP learning

The cost of explainability in artificial intelligence-enhanced electrocardiogram models.

Authors: Patlatzoglou, Konstantinos Pastika, Libor Barker, Joseph et al.

Source: NPJ Digital Medicine; 12/5/2025, Vol. 8 Issue 1, p1-13, 13p

Subject Terms: MORTALITY risk factors, DECISION support systems, RISK assessment, PEARSON correlation (Statistics), PREDICTION models, RECEIVER operating characteristic curves, RESEARCH funding, ARTIFICIAL intelligence, AUTOENCODERS, SEX distribution, AGE distribution, DESCRIPTIVE statistics, ELECTROCARDIOGRAPHY, LONGITUDINAL method, CONCEPTUAL structures, DEEP learning, DATA analysis software, REGRESSION analysis

Geographic Terms: MASSACHUSETTS

Improving the explainability of autoencoder factors for commodities through forecast-based Shapley values.

Authors: Cerqueti, Roy Iovanella, Antonio Mattera, Raffaele et al.

Source: Scientific Reports; 8/23/2024, Vol. 14 Issue 1, p1-13, 13p

Subject Terms: MACHINE learning, PRINCIPAL components analysis, FACTORING (Finance), COMMODITY exchanges, AUTOENCODERS