Cargando…

Predicting response to CCRT for esophageal squamous carcinoma by a radiomics-clinical SHAP model

BACKGROUND: Radical concurrent chemoradiotherapy (CCRT) is frequently used as the first-line treatment for patients with locally advanced esophageal cancer. Unfortunately, some patients respond poorly. To predict response to radical concurrent chemoradiotherapy in pre-treatment patients with esophag...

Descripción completa

Detalles Bibliográficos
Autores principales:	Cheng, Xu, Zhang, Yuxin, Zhu, Min, Sun, Ruixia, Liu, Lingling, Li, Xueling
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2023
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10544369/ https://www.ncbi.nlm.nih.gov/pubmed/37779188 http://dx.doi.org/10.1186/s12880-023-01089-0

Ejemplares similares

A Bayesian network meta-analysis of the primary definitive therapies for locoregionally advanced nasopharyngeal carcinoma: IC+CCRT, CCRT+AC, and CCRT alone
por: Zhang, Zhan-Jie, et al.
Publicado: (2022)

Predicting Disease-Free Survival With Multiparametric MRI-Derived Radiomic Signature in Cervical Cancer Patients Underwent CCRT
por: Liu, Bing, et al.
Publicado: (2022)

Long-term outcomes of neoadjuvant chemotherapy followed by concurrent chemoradiotherapy (CCRT) vs CCRT alone for nasopharyngeal carcinoma in the era of intensity-modulated radiation therapy using propensity score matching method
por: Chen, Xueling, et al.
Publicado: (2017)

DCE-MRI Quantitative Parameters as Predictors of Treatment Response in Patients With Locally Advanced Cervical Squamous Cell Carcinoma Underwent CCRT
por: Liu, Bing, et al.
Publicado: (2020)

GPUTreeShap: massively parallel exact calculation of SHAP scores for tree ensembles
por: Mitchell, Rory, et al.
Publicado: (2022)

Comparative Clinical Efficacy of ‘Concurrent Chemoradiotherapy (CCRT) and Anlotinib’ Than CCRT in Patients with Locally Advanced ESCC
por: Wang, Gang, et al.
Publicado: (2022)

Predicting response to immunotherapy plus chemotherapy in patients with esophageal squamous cell carcinoma using non-invasive Radiomic biomarkers
por: Zhu, Ying, et al.
Publicado: (2021)

A radiomics nomogram for predicting postoperative recurrence in esophageal squamous cell carcinoma
por: Tong, Yahan, et al.
Publicado: (2023)

Ultrasound-based radiomics XGBoost model to assess the risk of central cervical lymph node metastasis in patients with papillary thyroid carcinoma: Individual application of SHAP
por: Shi, Yan, et al.
Publicado: (2022)

Positional SHAP (PoSHAP) for Interpretation of machine learning models trained from biological sequences
por: Dickinson, Quinn, et al.
Publicado: (2022)

The CCRT: an inexpensive cosmic ray muon detector
por: Harpell, E, et al.
Publicado: (1995)

Computed Tomography-Based Radiomics in Predicting T Stage and Length of Esophageal Squamous Cell Carcinoma
por: Yang, Mingwei, et al.
Publicado: (2021)

Interpretable predictive model for shield attitude control performance based on XGboost and SHAP
por: Hu, Min, et al.
Publicado: (2022)

SERPINB5 Expression: Association with CCRT Response and Prognostic Value in Rectal Cancer
por: Chang, I-Wei, et al.
Publicado: (2018)

Unboxing Industry-Standard AI Models for Male Fertility Prediction with SHAP
por: GhoshRoy, Debasmita, et al.
Publicado: (2023)

Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT
por: Meng, Jie, et al.
Publicado: (2017)

Age plays an important role in the decision of definitive concurrent chemoradiotherapy (CCRT) for esophageal squamous cell carcinoma (ESCC): a propensity-score matched analysis of multicenter data (3JECROG R-02A)
por: Wang, Lan, et al.
Publicado: (2021)

The complete chloroplast genome of Alhagi sparsifolia Shap. (Leguminosae)
por: Jiang, Xi, et al.
Publicado: (2021)

CT-based radiomic signatures for prediction of pathologic complete response in esophageal squamous cell carcinoma after neoadjuvant chemoradiotherapy
por: Yang, Zhining, et al.
Publicado: (2019)

CT radiomics features of meso-esophageal fat in predicting overall survival of patients with locally advanced esophageal squamous cell carcinoma treated by definitive chemoradiotherapy
por: Yan, Shuo, et al.
Publicado: (2023)

Texture Analysis as Imaging Biomarker for recurrence in advanced cervical cancer treated with CCRT
por: Meng, Jie, et al.
Publicado: (2018)

Contrast-Enhanced CT-Based Radiomics Analysis in Predicting Lymphovascular Invasion in Esophageal Squamous Cell Carcinoma
por: Li, Yang, et al.
Publicado: (2021)

A Radiomics Nomogram for Non-Invasive Prediction of Progression-Free Survival in Esophageal Squamous Cell Carcinoma
por: Yan, Ting, et al.
Publicado: (2022)

SHAP and LIME: An Evaluation of Discriminative Power in Credit Risk
por: Gramegna, Alex, et al.
Publicado: (2021)

Radiomic analysis in contrast-enhanced CT: predict treatment response to chemoradiotherapy in esophageal carcinoma
por: Hou, Zhen, et al.
Publicado: (2017)

PPSW–SHAP: Towards Interpretable Cell Classification Using Tree-Based SHAP Image Decomposition and Restoration for High-Throughput Bright-Field Imaging
por: Goktas, Polat, et al.
Publicado: (2023)

An artificial neural network-based radiomics model for predicting the radiotherapy response of advanced esophageal squamous cell carcinoma patients: a multicenter study
por: Xie, Yuchen, et al.
Publicado: (2023)

DCE-MRI Perfusion and Permeability Parameters as predictors of tumor response to CCRT in Patients with locally advanced NSCLC
por: Tao, Xiuli, et al.
Publicado: (2016)

Predictive and Prognostic Value of Metabolic Tumor Volume (MTV) in Patients with Laryngeal Carcinoma Treated by Radiotherapy (RT) / Concurrent Chemoradiotherapy (CCRT)
por: Yabuki, Kenichiro, et al.
Publicado: (2015)

Corrigendum: Contrast-Enhanced CT-Based Radiomics Analysis in Predicting Lymphovascular Invasion in Esophageal Squamous Cell Carcinoma
por: Li, Yang, et al.
Publicado: (2021)

Predicting the efficacy of radiotherapy for esophageal squamous cell carcinoma based on enhanced computed tomography radiomics and combined models
por: Liu, Jihui, et al.
Publicado: (2023)

An Interpretable Prediction Model for Identifying N(7)-Methylguanosine Sites Based on XGBoost and SHAP
por: Bi, Yue, et al.
Publicado: (2020)

Assessment of Intratumoral and Peritumoral Computed Tomography Radiomics for Predicting Pathological Complete Response to Neoadjuvant Chemoradiation in Patients With Esophageal Squamous Cell Carcinoma
por: Hu, Yihuai, et al.
Publicado: (2020)

Response Prediction to Concurrent Chemoradiotherapy in Esophageal Squamous Cell Carcinoma Using Delta-Radiomics Based on Sequential Whole-Tumor ADC Map
por: An, Dianzheng, et al.
Publicado: (2022)

Radiomics Analysis of Lymph Nodes with Esophageal Squamous Cell Carcinoma Based on Deep Learning
por: Chen, Li, et al.
Publicado: (2022)

XGBoost-SHAP-based interpretable diagnostic framework for alzheimer’s disease
por: Yi, Fuliang, et al.
Publicado: (2023)

High SPINK4 Expression Predicts Poor Outcomes among Rectal Cancer Patients Receiving CCRT
por: Chen, Tzu-Ju, et al.
Publicado: (2021)

A nomogram based on pretreatment CT radiomics features for predicting complete response to chemoradiotherapy in patients with esophageal squamous cell cancer
por: Luo, He-San, et al.
Publicado: (2020)

A radiomics nomogram based on contrast-enhanced CT for preoperative prediction of Lymphovascular invasion in esophageal squamous cell carcinoma
por: Wang, Yating, et al.
Publicado: (2023)

Adjuvant concurrent chemoradiation therapy (CCRT) alone versus CCRT followed by adjuvant chemotherapy: Which is better in patients with radically resected extrahepatic biliary tract cancer?: a non-randomized, single center study
por: Lim, Kyu-Hyoung, et al.
Publicado: (2009)

Cannot write session to /tmp/vufind_sessions/sess_s1piojbqm7b9soa4t7jja0gffs