Cargando…

Cycle-consistent adversarial networks improves generalizability of radiomics model in grading meningiomas on external validation

The heterogeneity of MRI is one of the major reasons for decreased performance of a radiomics model on external validation, limiting the model’s generalizability and clinical application. We aimed to establish a generalizable radiomics model to predict meningioma grade on external validation through...

Descripción completa

Detalles Bibliográficos
Autores principales:	Park, Yae Won, Shin, Seo Jeong, Eom, Jihwan, Lee, Heirim, You, Seng Chan, Ahn, Sung Soo, Lim, Soo Mee, Park, Rae Woong, Lee, Seung-Koo
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Nature Publishing Group UK 2022
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9055063/ https://www.ncbi.nlm.nih.gov/pubmed/35488007 http://dx.doi.org/10.1038/s41598-022-10956-9

Ejemplares similares

An interpretable radiomics model to select patients for radiotherapy after surgery for WHO grade 2 meningiomas
por: Park, Chae Jung, et al.
Publicado: (2022)

An interpretable multiparametric radiomics model for the diagnosis of schizophrenia using magnetic resonance imaging of the corpus callosum
por: Bang, Minji, et al.
Publicado: (2021)

An interpretable multiparametric radiomics model of basal ganglia to predict dementia conversion in Parkinson’s disease
por: Park, Chae Jung, et al.
Publicado: (2023)

Differentiation of recurrent glioblastoma from radiation necrosis using diffusion radiomics with machine learning model development and external validation
por: Park, Yae Won, et al.
Publicado: (2021)

Comparison of Diagnostic Performance of Two-Dimensional and Three-Dimensional Fractal Dimension and Lacunarity Analyses for Predicting the Meningioma Grade
por: Kim, Soopil, et al.
Publicado: (2020)

Radiomics MRI Phenotyping with Machine Learning to Predict the Grade of Lower-Grade Gliomas: A Study Focused on Nonenhancing Tumors
por: Park, Yae Won, et al.
Publicado: (2019)

Preoperative Prediction of Meningioma Consistency via Machine Learning-Based Radiomics
por: Zhai, Yixuan, et al.
Publicado: (2021)

A Radiomics-Based Model with the Potential to Differentiate Growth Hormone Deficiency and Idiopathic Short Stature on Sella MRI
por: Lee, Taeyoun, et al.
Publicado: (2022)

Reproducibility and Generalizability in Radiomics Modeling: Possible Strategies in Radiologic and Statistical Perspectives
por: Park, Ji Eun, et al.
Publicado: (2019)

Full-text chemical identification with improved generalizability and tagging consistency
por: Kim, Hyunjae, et al.
Publicado: (2022)

How Consistent Are Challenge and Threat Evaluations? A Generalizability Analysis
por: Moore, Lee J., et al.
Publicado: (2019)

Quality Reporting of Radiomics Analysis in Mild Cognitive Impairment and Alzheimer's Disease: A Roadmap for Moving Forward
por: Won, So Yeon, et al.
Publicado: (2020)

Three-dimensional fractal dimension and lacunarity features may noninvasively predict TERT promoter mutation status in grade 2 meningiomas
por: Won, So Yeon, et al.
Publicado: (2022)

Radiomics machine learning study with a small sample size: Single random training-test set split may lead to unreliable results
por: An, Chansik, et al.
Publicado: (2021)

Radiographic prediction of meningioma grade by semantic and radiomic features
por: Coroller, Thibaud P., et al.
Publicado: (2017)

Dual-Level Augmentation Radiomics Analysis for Multisequence MRI Meningioma Grading
por: Cai, Zongyou, et al.
Publicado: (2023)

Preoperative prediction of Ki-67 and p53 status in meningioma using a multiparametric MRI-based clinical-radiomic model
por: Moon, Chung-Man, et al.
Publicado: (2023)

Changes in radiomic and radiologic features in meningiomas after radiation therapy
por: Jo, Sang Won, et al.
Publicado: (2023)

A Radiomics-Based Model for Potentially More Accurate Identification of Subtypes of Breast Cancer Brain Metastases
por: Cho, Seonghyeon, et al.
Publicado: (2023)

Quality of Radiomics Research on Brain Metastasis: A Roadmap to Promote Clinical Translation
por: Park, Chae Jung, et al.
Publicado: (2022)

Data augmentation using generative adversarial networks (CycleGAN) to improve generalizability in CT segmentation tasks
por: Sandfort, Veit, et al.
Publicado: (2019)

Translation of paired fundus photographs to fluorescein angiographs with energy-based cycle-consistent adversarial networks
por: Kang, Tae Seen, et al.
Publicado: (2023)

Multiple meningiomas consisting of fibrous meningioma, transitional meningioma, and meningotheliomatous meningioma in one adult patient
por: Yudoyono, Farid, et al.
Publicado: (2015)

Test–Retest Data for Radiomics Feature Stability Analysis: Generalizable or Study-Specific?
por: van Timmeren, Janna E., et al.
Publicado: (2016)

Extensions of the External Validation for Checking Learned Model Interpretability and Generalizability
por: Ho, Sung Yang, et al.
Publicado: (2020)

Non-contrast CT synthesis using patch-based cycle-consistent generative adversarial network (Cycle-GAN) for radiomics and deep learning in the era of COVID-19
por: Kalantar, Reza, et al.
Publicado: (2023)

Radiomics and Deep Learning: Hepatic Applications
por: Park, Hyo Jung, et al.
Publicado: (2020)

Radiomics-Based Prediction of TERT Promotor Mutations in Intracranial High-Grade Meningiomas
por: Akkurt, Burak Han, et al.
Publicado: (2023)

Adversarial training with cycle consistency for unsupervised super-resolution in endomicroscopy
por: Ravì, Daniele, et al.
Publicado: (2019)

Surgical Outcomes of Sphenoid Wing Meningioma with Periorbital Invasion
por: Park, Ga-On, et al.
Publicado: (2022)

The Current State of Radiomics for Meningiomas: Promises and Challenges
por: Gu, Hao, et al.
Publicado: (2020)

Molecular characteristics of meningiomas
por: Lee, Young Suk, et al.
Publicado: (2020)

Limited generalizability of deep learning algorithm for pediatric pneumonia classification on external data
por: Xin, Kevin Z., et al.
Publicado: (2021)

Generalizable and Automated Classification of TNM Stage from Pathology Reports with External Validation
por: Kefeli, Jenna, et al.
Publicado: (2023)

Lund jet images from generative and cycle-consistent adversarial networks
por: Dreyer, Frederic Alexandre
Publicado: (2019)

Correction to: Unpaired Image-to-Image Translation Using Adversarial Consistency Loss
por: Zhao, Yihao, et al.
Publicado: (2021)

A Multi-Center, Multi-Vendor Study to Evaluate the Generalizability of a Radiomics Model for Classifying Prostate cancer: High Grade vs. Low Grade
por: Castillo T., Jose M., et al.
Publicado: (2021)

An Unusual Cervical Spinal Meningioma in a Child
por: Cho, Hyok-Rae, et al.
Publicado: (2013)

Meningioma Radiomics: At the Nexus of Imaging, Pathology and Biomolecular Characterization
por: Ugga, Lorenzo, et al.
Publicado: (2022)

Generalizability of Cardiovascular Disease Clinical Prediction Models: 158 Independent External Validations of 104 Unique Models
por: Gulati, Gaurav, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_ucbp9l7htm844kh3ej6mtkepls