Výsledky vyhledávání - normative deep autoencoder

A generalizable normative deep autoencoder for brain morphological anomaly detection: application to the multi-site StratiBip dataset on bipolar disorder in an external validation framework.

Autoři: Sampaio IW Tassi E Bellani M a další

Zdroj: Artificial intelligence in medicine [Artif Intell Med] 2025 Mar; Vol. 161, pp. 103063. Date of Electronic Publication: 2025 Jan 02.

Způsob vydávání: Journal Article; Validation Study; Multicenter Study; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't

Informace o časopise: Publisher: Elsevier Science Publishing Country of Publication: Netherlands NLM ID: 8915031 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-2860 (Electronic) Linking ISSN: 09333657 NLM ISO Abbreviation: Artif Intell Med Subsets: MEDLINE

Výrazy ze slovníku MeSH: Bipolar Disorder*/diagnostic imaging , Bipolar Disorder*/pathology , Brain*/diagnostic imaging , Brain*/pathology, Humans ; Male ; Female ; Magnetic Resonance Imaging ; Adult ; Connectome ; Case-Control Studies ; Autoencoder

A generalizable normative deep autoencoder for brain morphological anomaly detection: application to the multi-site StratiBip dataset on bipolar disorder in an external validation framework

Autoři: Sampaio, Inês Won Tassi, Emma Bellani, Marcella a další

Zdroj: bioRxiv

Témata: Male, Adult, Bipolar Disorder, Brain, Anomaly detection, Autoencoder, Magnetic Resonance Imaging, Article, Brain MRI, Multi-site harmonization, Normative modelling, Psychiatric disorders, Case-Control Studies, Connectome, Humans, Female

Popis souboru: application/pdf

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/39282436
https://pubmed.ncbi.nlm.nih.gov/39837135
https://hdl.handle.net/20.500.11768/180659
https://doi.org/10.1016/j.artmed.2024.103063
https://hdl.handle.net/2434/1158302
https://doi.org/10.1016/j.artmed.2024.103063

Deep reinforcement learning and convolutional autoencoders for anomaly detection of congenital inner ear malformations in clinical CT images

Autoři: López Diez, Paula Sundgaard, Josefine Vilsbøll Margeta, Jan a další

Zdroj: López Diez , P , Sundgaard , J V , Margeta , J , Diab , K , Patou , F & Paulsen , R R 2024 , ' Deep reinforcement learning and convolutional autoencoders for anomaly detection of congenital inner ear malformations in clinical CT images ' , Computerized Medical Imaging and Graphics , vol. 113 , 102343 .

Témata: Anomaly detection, Cochlear implant, Computed tomography, Congenital malformation, Deep reinforcement learning, article

URL: https://orbit.dtu.dk/en/publications/2e1afbb8-5d4e-410d-a7cb-827a6329a078
https://doi.org/10.1016/j.compmedimag.2024.102343
https://backend.orbit.dtu.dk/ws/files/351811363/1-s2.0-S089561112400020X-main.pdf

Appendix A1 and Appendix A2.

Autoři: Catalina Saini Cristian Salazar-Vilches Caroline C.V. Blanchard a další

Témata: Cell Biology, Neuroscience, Physiology, Biotechnology, Mental Health, novel treatment approaches, extrapyramidal movement sub, extrapyramidal movement disorders, exploratory analysis showed, approach enables identification, subtle tissue anomalies, normative deep autoencoder, influential features contributing, features &# 8217, apparent diffusion coefficient, cerebellar white matter, cerebellar gray matter, learning , +features%22">xlink "> features, telangiectasia using deep, shap scores revealed, pallidum perfusion underestimated, diffusion reconstruction errors, %22">xlink ">, diffusion features, cerebellar diffusion, subcortical anomalies, reconstruction errors, normative self, perfusion features

Relation: https://figshare.com/articles/journal_contribution/Appendix_A1_and_Appendix_A2_/30012420

Dostupnost: https://doi.org/10.1371/journal.pone.0328828.s002
https://figshare.com/articles/journal_contribution/Appendix_A1_and_Appendix_A2_/30012420

Personalized MRI-based characterization of subcortical anomalies in Ataxia-Telangiectasia using deep-learning.

Autoři: Saini, Catalina Salazar-Vilches, Cristian Blanchard, Caroline C.V. a další

Zdroj: PLoS ONE; 8/29/2025, Vol. 20 Issue 8, p1-14, 14p

Témata: ATAXIA telangiectasia, MAGNETIC resonance imaging, PERFUSION, BASAL ganglia, DEEP learning, CEREBELLUM degeneration, DIFFUSION coefficients, BASAL ganglia diseases

Microstructural mapping of neural pathways in Alzheimers disease using macrostructure-informed normative tractometry.

Autoři: Feng, Yixue Chandio, Bramsh Villalon-Reina, Julio a další

Zdroj: Alzheimers & Dementia: The Journal of the Alzheimers Association. 21(1)

Témata: Alzheimers disease, anomaly detection, deep generative models, diffusion magnetic resonance imaging, normative modeling, tractometry, transfer learning, Humans, Alzheimer Disease, Diffusion Tensor Imaging, White Matter, Aged, Cognitive Dysfunction, Male, Female, Neural Pathways, Brain, India, Brain Mapping, Diffusion Magnetic Resonance Imaging, North America, Cohort Studies

Popis souboru: application/pdf

Přístupová URL adresa: https://escholarship.org/uc/item/0ht70274
https://escholarship.org/content/qt0ht70274/qt0ht70274.pdf

Novelty Detection using Deep Normative Modeling for IMU-Based Abnormal Movement Monitoring in Parkinson’s Disease and Autism Spectrum Disorders

Autoři: Nastaran Mohammadian Rad Twan van Laarhoven Cesare Furlanello a další

Zdroj: Sensors, Vol 18, Iss 10, p 3533 (2018)

Témata: novelty detection, deep learning, normative modeling, denoising autoencoders, Parkinson’s disease, autism spectrum disorder, stereotypical motor movements, freezing of gait, Chemical technology, TP1-1185

Popis souboru: electronic resource

Relation: http://www.mdpi.com/1424-8220/18/10/3533; https://doaj.org/toc/1424-8220

Přístupová URL adresa: https://doaj.org/article/dc715b28d4d346c8baeb74991d5734be

Normative model for the diagnosis of neuropsychiatric disorders using deep learning methods

Autoři: Saraiva, Duarte Filipe Oliveira Ferreira, Hugo Alexandre Repositório Científico de Acesso Aberto da ULisboa

Přispěvatelé: Saraiva, Duarte Filipe Oliveira Ferreira, Hugo Alexandre Repositório Científico de Acesso Aberto da ULisboa

Zdroj: urn:tid:203219252

Témata: Modelo Normativo, Redes Cerebrais Funcionais, Perturbações Neuropsiquiátricas, Conectividade Funcional, Aprendizagem Profunda, Teses de mestrado - 2022

Popis souboru: application/pdf

Dostupnost: http://hdl.handle.net/10451/51226

Normative Modeling via Conditional Variational Autoencoder and Adversarial Learning to Identify Brain Dysfunction in Alzheimer's Disease

Autoři: Wang, Xuetong Zhao, Kanhao Zhou, Rong a další

Témata: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Quantitative Biology - Quantitative Methods, 68T07, 62P10, 92C55, I.2, J.3, text

URL: http://arxiv.org/abs/2211.08982

Path-masked Autoencoder Guiding Unsupervised Attribute Graph Node Clustering

Autoři: DING Xinyu, KONG Bing, CHEN Hongmei, BAO Chongming, ZHOU Lihua

Zdroj: Jisuanji kexue, Vol 52, Iss 1, Pp 160-169 (2025)

Témata: deep graph clustering, unsupervised learning, feature integration, module maximization, self-training for clustering, Computer software, QA76.75-76.765, Technology (General), T1-995

Popis souboru: electronic resource

Relation: https://www.jsjkx.com/fileup/1002-137X/PDF/1002-137X-2025-52-1-160.pdf; https://doaj.org/toc/1002-137X

Přístupová URL adresa: https://doaj.org/article/5bd751898a40453ebf0d8c87286751a7

Normative Modeling using Multimodal Variational Autoencoders to Identify Abnormal Brain Structural Patterns in Alzheimer Disease

Autoři: Kumar, Sayantan Payne, Philip Sotiras, Aristeidis

Témata: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2110.04903

Inclusivity-in-global-research-questionnaire.

Autoři: Catalina Saini Cristian Salazar-Vilches Caroline C.V. Blanchard a další

Témata: Cell Biology, Neuroscience, Physiology, Biotechnology, Mental Health, novel treatment approaches, extrapyramidal movement sub, extrapyramidal movement disorders, exploratory analysis showed, approach enables identification, subtle tissue anomalies, normative deep autoencoder, influential features contributing, features &# 8217, apparent diffusion coefficient, cerebellar white matter, cerebellar gray matter, learning , +features%22">xlink "> features, telangiectasia using deep, shap scores revealed, pallidum perfusion underestimated, diffusion reconstruction errors, %22">xlink ">, diffusion features, cerebellar diffusion, subcortical anomalies, reconstruction errors, normative self, perfusion features

Dostupnost: https://doi.org/10.1371/journal.pone.0328828.s003
https://figshare.com/articles/journal_contribution/Inclusivity-in-global-research-questionnaire_/30012423

Uncertainty in latent representations of variational autoencoders optimized for visual tasks

Autoři: Catoni, Josefina Martos, Domonkos Csikor, Ferenc a další

Témata: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2404.15390

A generalizable normative deep autoencoder for brain morphological anomaly detection: application to the multi-site StratiBip dataset on bipolar disorder in an external validation framework.

Zdroj: Drug Week. 9/27/2024, p122-122. 1p.

Deep learning based normative models identify structures that become abnormal with Alzheimer's disease.

Autoři: Jaramillo, Camilo Trujillo, Maria Bernal, Jose

Zdroj: Alzheimer's & Dementia: The Journal of the Alzheimer's Association. Dec2023 Supplement 17, Vol. 19, p1-4. 4p.

Anomaly Detection in Satellite Imagery Using Deep Autoencoders.

Autoři: Mohammed, Ayat Jasim Khraibet, Ali Raheem Majeed, Huda Lafta a další

Zdroj: Fusion: Practice & Applications; 2025, Vol. 20 Issue 1, p166-178, 13p

Témata: REMOTE-sensing images, EMERGENCY management, ENVIRONMENTAL monitoring, ENVIRONMENTAL disasters, DIRECT broadcast satellite television

Deep normative modelling reveals insights into early-stage Alzheimer's disease using multi-modal neuroimaging data.

Autoři: Lawry Aguila, Ana Lorenzini, Luigi Janahi, Mohammed a další

Zdroj: Alzheimer's Research & Therapy; 5/15/2025, Vol. 17 Issue 1, p1-13, 13p

Témata: MEDICAL sciences, ALZHEIMER'S disease, COGNITIVE psychology, CLINICAL health psychology, COGNITIVE ability

Normative model detects abnormal functional connectivity in psychiatric disorders

Autoři: Duarte Oliveira-Saraiva Hugo Alexandre Ferreira

Zdroj: Frontiers in Psychiatry, Vol 14 (2023)

Témata: normative model, functional brain network, deep learning, psychiatric disorders, functional connectivity, Psychiatry, RC435-571

Popis souboru: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1068397/full; https://doaj.org/toc/1664-0640

Přístupová URL adresa: https://doaj.org/article/ae55a5e7fc2b4a2fbd6315cd6e1bec67

Using deep autoencoders to identify abnormal brain structural patterns in neuropsychiatric disorders: A large‐scale multi‐sample study.

Autoři: Pinaya, Walter H. L. Mechelli, Andrea Sato, João R.

Zdroj: Human Brain Mapping; Feb2019, Vol. 40 Issue 3, p944-954, 11p

Role of Deep Learning in Neurodevelopmental Disorders: A Narrative Review.

Autoři: Chacko, Nilah Ans Veedu, Nimmi Puthan Panayan, Abhinav a další

Zdroj: Journal of Clinical & Diagnostic Research; Nov2025, Vol. 19 Issue 11, p1-8, 8p

Témata: DEEP learning, AUTISM spectrum disorders, PEDIATRIC neurology, ATTENTION-deficit hyperactivity disorder, DIAGNOSTIC examinations, NEURAL development