Cargando…

Application of radiomics and machine learning in head and neck cancers

With the continuous development of medical image informatics technology, more and more high-throughput quantitative data could be extracted from digital medical images, which has resulted in a new kind of omics-Radiomics. In recent years, in addition to genomics, proteomics and metabolomics, radiomi...

Descripción completa

Detalles Bibliográficos
Autores principales:	Peng, Zhouying, Wang, Yumin, Wang, Yaxuan, Jiang, Sijie, Fan, Ruohao, Zhang, Hua, Jiang, Weihong
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Ivyspring International Publisher 2021
Materias:	Review
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7893590/ https://www.ncbi.nlm.nih.gov/pubmed/33613106 http://dx.doi.org/10.7150/ijbs.55716

Ejemplares similares

Comparing the Effectiveness of Endoscopic Surgeries With Intensity-Modulated Radiotherapy for Recurrent rT3 and rT4 Nasopharyngeal Carcinoma: A Meta-Analysis
por: Peng, Zhouying, et al.
Publicado: (2021)

Preliminary Efficacy Report and Prognosis Analysis of Endoscopic Endonasal Nasopharyngectomy for Recurrent Nasopharyngeal Carcinoma
por: Peng, Zhouying, et al.
Publicado: (2021)

Hemangiopericytoma/solitary fibrous tumor of the cranial base: a case series and literature review
por: Peng, Zhouying, et al.
Publicado: (2022)

Immune Microenvironment Change and Involvement of Circular RNAs in TIL Cells of Recurrent Nasopharyngeal Carcinoma
por: Wang, Yumin, et al.
Publicado: (2021)

Precision Endonasal Endoscopic Surgery of the Frontal Recess Cells and Frontal Sinus Guided by the Natural Sinus Drainage Pathway
por: Peng, Zhouying, et al.
Publicado: (2022)

Salvage Endoscopic Skull Base Surgery: Another Treatment Option After Immunotherapy for Recurrent Nasopharyngeal Carcinoma
por: Peng, Zhouying, et al.
Publicado: (2022)

Advances of DNA Damage Repair-Related Drugs and Combination With Immunotherapy in Tumor Treatment
por: Wang, Yumin, et al.
Publicado: (2022)

Radiomics and Machine Learning for Radiotherapy in Head and Neck Cancers
por: Giraud, Paul, et al.
Publicado: (2019)

Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer
por: Parmar, Chintan, et al.
Publicado: (2015)

Treatment of Recurrent Nasopharyngeal Carcinoma: A Sequential Challenge
por: Peng, Zhouying, et al.
Publicado: (2022)

The progress of multimodal imaging combination and subregion based radiomics research of cancers
por: Zhang, Luyuan, et al.
Publicado: (2022)

Improvements and challenges of tissue preparation for spatial transcriptome analysis of skull base tumors
por: Fang, Yan, et al.
Publicado: (2023)

Outcomes of endoscopic and open resection of sinonasal malignancies: a systematic review and meta-analysis
por: Jiang, Sijie, et al.
Publicado: (2021)

Machine Learning Applications in Head and Neck Radiation Oncology: Lessons From Open-Source Radiomics Challenges
por: Elhalawani, Hesham, et al.
Publicado: (2018)

Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics
por: Huynh, Bao Ngoc, et al.
Publicado: (2023)

Utility of adding Radiomics to clinical features in predicting the outcomes of radiotherapy for head and neck cancer using machine learning
por: Gangil, Tarun, et al.
Publicado: (2022)

Radiomics in Head and Neck Cancer Outcome Predictions
por: Gonçalves, Maria, et al.
Publicado: (2022)

Machine Learning-Based Radiomics Predicts Radiotherapeutic Response in Patients With Acromegaly
por: Fan, Yanghua, et al.
Publicado: (2019)

Investigation of Radiation-Induced Toxicity in Head and Neck Cancer Patients through Radiomics and Machine Learning: A Systematic Review
por: Carbonara, Roberta, et al.
Publicado: (2021)

Olfactory Neuroblastoma: Surgical Treatment Experience of 42 Cases
por: Cai, Xiao, et al.
Publicado: (2022)

Diagnostic Utility of Radiomics in Thyroid and Head and Neck Cancers
por: Gul, Maryam, et al.
Publicado: (2021)

Framework for Machine Learning of CT and PET Radiomics to Predict Local Failure after Radiotherapy in Locally Advanced Head and Neck Cancers
por: Devakumar, Devadhas, et al.
Publicado: (2021)

Deep versus Handcrafted Tensor Radiomics Features: Prediction of Survival in Head and Neck Cancer Using Machine Learning and Fusion Techniques
por: Salmanpour, Mohammad R., et al.
Publicado: (2023)

Radiomics Applications in Head and Neck Tumor Imaging: A Narrative Review
por: Tortora, Mario, et al.
Publicado: (2023)

Site-Specific Variation in Radiomic Features of Head and Neck Squamous Cell Carcinoma and Its Impact on Machine Learning Models
por: Liu, Xiaoyang, et al.
Publicado: (2021)

Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer
por: Vallières, Martin, et al.
Publicado: (2017)

Machine Learning: Applications and Advanced Progresses of Radiomics in Endocrine Neoplasms
por: Wang, Yong, et al.
Publicado: (2021)

Exploring Applications of Radiomics in Magnetic Resonance Imaging of Head and Neck Cancer: A Systematic Review
por: Jethanandani, Amit, et al.
Publicado: (2018)

Machine Learning–Guided Adjuvant Treatment of Head and Neck Cancer
por: Howard, Frederick Matthew, et al.
Publicado: (2020)

Exosomes Derived hsa-miR-4669 as a Novel Biomarker for Early Predicting the Response of Subcutaneous Immunotherapy in Pediatric Allergic Rhinitis
por: Jiang, Sijie, et al.
Publicado: (2022)

Current Role of Delta Radiomics in Head and Neck Oncology
por: Marcu, David C., et al.
Publicado: (2023)

Privacy-preserving distributed learning of radiomics to predict overall survival and HPV status in head and neck cancer
por: Bogowicz, Marta, et al.
Publicado: (2020)

Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics
por: Kazmierski, Michal, et al.
Publicado: (2023)

The importance of feature aggregation in radiomics: a head and neck cancer study
por: Fontaine, Pierre, et al.
Publicado: (2020)

Longitudinal and Multimodal Radiomics Models for Head and Neck Cancer Outcome Prediction
por: Starke, Sebastian, et al.
Publicado: (2023)

Applications of radiomics and machine learning for radiotherapy of malignant brain tumors
por: Kocher, Martin, et al.
Publicado: (2020)

Radiomics and machine learning applications in rectal cancer: Current update and future perspectives
por: Stanzione, Arnaldo, et al.
Publicado: (2021)

Elevated ALCAM Expression Associated with Endotypes and Postoperative Recurrence in Chronic Rhinosinusitis with Nasal Polyps
por: Zhang, Hua, et al.
Publicado: (2022)

Multi-centre radiomics for prediction of recurrence following radical radiotherapy for head and neck cancers: Consequences of feature selection, machine learning classifiers and batch-effect harmonization
por: Varghese, Amal Joseph, et al.
Publicado: (2023)

Radiomic feature clusters and Prognostic Signatures specific for Lung and Head & Neck cancer
por: Parmar, Chintan, et al.
Publicado: (2015)

Cannot write session to /tmp/vufind_sessions/sess_j7dmch8c4n7kouv2mhthqnjum1