Cargando…

Prediction Model of Hemorrhage Transformation in Patient with Acute Ischemic Stroke Based on Multiparametric MRI Radiomics and Machine Learning

Intravenous thrombolysis is the most commonly used drug therapy for patients with acute ischemic stroke, which is often accompanied by complications of intracerebral hemorrhage transformation (HT). This study proposed to build a reliable model for pretreatment prediction of HT. Specifically, 5400 ra...

Descripción completa

Detalles Bibliográficos
Autores principales:	Meng, Yucong, Wang, Haoran, Wu, Chuanfu, Liu, Xiaoyu, Qu, Linhao, Shi, Yonghong
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2022
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9313447/ https://www.ncbi.nlm.nih.gov/pubmed/35884664 http://dx.doi.org/10.3390/brainsci12070858

Ejemplares similares

Prediction of Hemorrhagic Transformation after Ischemic Stroke Using Machine Learning
por: Choi, Jeong-Myeong, et al.
Publicado: (2021)

Repeatability of Multiparametric Prostate MRI Radiomics Features
por: Schwier, Michael, et al.
Publicado: (2019)

Prognosis of ischemic stroke predicted by machine learning based on multi-modal MRI radiomics
por: Yu, Huan, et al.
Publicado: (2023)

Radiomics and Machine Learning with Multiparametric Breast MRI for Improved Diagnostic Accuracy in Breast Cancer Diagnosis
por: Daimiel Naranjo, Isaac, et al.
Publicado: (2021)

Integrated radiomic framework for breast cancer and tumor biology using advanced machine learning and multiparametric MRI
por: Parekh, Vishwa S., et al.
Publicado: (2017)

Hemorrhagic Transformation of Ischemic Strokes
por: Kovács, Kitti Bernadett, et al.
Publicado: (2023)

Radiomics-based infarct features on CT predict hemorrhagic transformation in patients with acute ischemic stroke
por: Xie, Gang, et al.
Publicado: (2022)

Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization
por: Toivonen, Jussi, et al.
Publicado: (2019)

Multiparametric MRI and Machine Learning Based Radiomic Models for Preoperative Prediction of Multiple Biological Characteristics in Prostate Cancer
por: Fan, Xuhui, et al.
Publicado: (2022)

Breast Lesion Classification with Multiparametric Breast MRI Using Radiomics and Machine Learning: A Comparison with Radiologists’ Performance
por: Daimiel Naranjo, Isaac, et al.
Publicado: (2022)

Prediction of recurrence of ischemic stroke within 1 year of discharge based on machine learning MRI radiomics
por: Liu, Jianmo, et al.
Publicado: (2023)

Radiomics-Based Detection of Radionecrosis Using Harmonized Multiparametric MRI
por: Acquitter, Clément, et al.
Publicado: (2022)

Machine learning-based multiparametric MRI radiomics for predicting poor responders after neoadjuvant chemoradiotherapy in rectal Cancer patients
por: Wang, Jia, et al.
Publicado: (2022)

Non-Invasive Prediction of Survival Time of Midline Glioma Patients Using Machine Learning on Multiparametric MRI Radiomics Features
por: Deng, Da-Biao, et al.
Publicado: (2022)

Preoperative Prediction of Microsatellite Instability in Rectal Cancer Using Five Machine Learning Algorithms Based on Multiparametric MRI Radiomics
por: Zhang, Yang, et al.
Publicado: (2023)

Machine Learning-Based Model for Prediction of Hemorrhage Transformation in Acute Ischemic Stroke After Alteplase
por: Xu, Yanan, et al.
Publicado: (2022)

Multiparametric MRI and Radiomics in Prostate Cancer: A Review of the Current Literature
por: Midiri, Federico, et al.
Publicado: (2021)

Radiomics Analysis of Multiparametric MRI for Prediction of Synchronous Lung Metastases in Osteosarcoma
por: Luo, Zhendong, et al.
Publicado: (2022)

Frequency and determinants for hemorrhagic transformation of posterior cerebral stroke: Posterior ischemic stroke and hemorrhagic transformation
por: Valentino, Francesca, et al.
Publicado: (2017)

A Multiparametric MRI-Based Radiomics Analysis to Efficiently Classify Tumor Subregions of Glioblastoma: A Pilot Study in Machine Learning
por: Chiu, Fang-Ying, et al.
Publicado: (2021)

Beyond Multiparametric MRI and towards Radiomics to Detect Prostate Cancer: A Machine Learning Model to Predict Clinically Significant Lesions
por: Gaudiano, Caterina, et al.
Publicado: (2022)

Hemorrhagic Transformation in Ischemic Stroke and the Role of Inflammation
por: Spronk, Elena, et al.
Publicado: (2021)

Machine Learning-Based Analysis of MR Multiparametric Radiomics for the Subtype Classification of Breast Cancer
por: Xie, Tianwen, et al.
Publicado: (2019)

The Stress Hyperglycemia Ratio is Associated with Hemorrhagic Transformation in Patients with Acute Ischemic Stroke
por: Yuan, Chengxiang, et al.
Publicado: (2021)

Deep learning and radiomics to predict the mitotic index of gastrointestinal stromal tumors based on multiparametric MRI
por: Yang, Linsha, et al.
Publicado: (2022)

Multiparametric MRI Features Predict the SYP Gene Expression in Low-Grade Glioma Patients: A Machine Learning-Based Radiomics Analysis
por: Xiao, Zheng, et al.
Publicado: (2021)

High ratio of monocytes to high-density lipoprotein is associated with hemorrhagic transformation in acute ischemic stroke patients on intravenous thrombolysis
por: Xia, Lingfan, et al.
Publicado: (2022)

Multiparametric Magnetic Resonance Imaging for Prediction of Parenchymal Hemorrhage in Acute Ischemic Stroke After Reperfusion Therapy
por: Nael, Kambiz, et al.
Publicado: (2017)

Radiomics-based machine learning analysis and characterization of breast lesions with multiparametric diffusion-weighted MR
por: Sun, Kun, et al.
Publicado: (2021)

High Neutrophil-to-Platelet Ratio Is Associated With Hemorrhagic Transformation in Patients With Acute Ischemic Stroke
por: He, Weilei, et al.
Publicado: (2019)

High fibrinogen‐to‐albumin ratio is associated with hemorrhagic transformation in acute ischemic stroke patients
por: Ruan, Yiting, et al.
Publicado: (2020)

Radiomics-based prediction of hemorrhage expansion among patients with thrombolysis/thrombectomy related-hemorrhagic transformation using machine learning
por: Liu, Junfeng, et al.
Publicado: (2021)

Hemorrhagic Transformation After Ischemic Stroke: Mechanisms and Management
por: Hong, Ji Man, et al.
Publicado: (2021)

Multiparametric MRI: From Simultaneous Rapid Acquisition Methods and Analysis Techniques Using Scoring, Machine Learning, Radiomics, and Deep Learning to the Generation of Novel Metrics
por: Hagiwara, Akifumi, et al.
Publicado: (2023)

MRI arterial spin labeling in evaluating hemorrhagic transformation following endovascular recanalization of subacute ischemic stroke
por: Wu, Liheng, et al.
Publicado: (2023)

Radiomics Analysis of Multiparametric MRI for the Preoperative Prediction of Lymph Node Metastasis in Cervical Cancer
por: Hou, Lina, et al.
Publicado: (2020)

Radiomics based on multiparametric MRI for extrathyroidal extension feature prediction in papillary thyroid cancer
por: Wei, Ran, et al.
Publicado: (2021)

A clinical–radiomics model based on noncontrast computed tomography to predict hemorrhagic transformation after stroke by machine learning: a multicenter study
por: Ren, Huanhuan, et al.
Publicado: (2023)

Machine Learning Based on a Multiparametric and Multiregional Radiomics Signature Predicts Radiotherapeutic Response in Patients with Glioblastoma
por: Pan, Zi-Qi, et al.
Publicado: (2020)

Comparison of machine learning algorithms to predict clinically significant prostate cancer of the peripheral zone with multiparametric MRI using clinical assessment categories and radiomic features
por: Bernatz, Simon, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_fpi5kp9ten9e4f7qian77pt7kd