Outcome prediction in head and neck cancer patients using machine learning methods

Mapping Intimacies ◽

10.17077/etd.wr7nz268 ◽

2014 ◽

Author(s):

David John Dellsperger

Keyword(s):

Machine Learning ◽

Head And Neck Cancer ◽

Head And Neck ◽

Cancer Patients ◽

Neck Cancer ◽

Outcome Prediction ◽

Learning Methods ◽

Machine Learning Methods

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Machine Learning Methods Uncover Radio-Morphologic Dose Patterns in Salivary Glands That Predict Xerostomia in Head and Neck Cancer Patients

International Journal of Radiation Oncology*Biology*Physics ◽

10.1016/j.ijrobp.2018.07.125 ◽

2018 ◽

Vol 102 (3) ◽

pp. S212 ◽

Author(s):

T.R. McNutt ◽

W. Jiang ◽

P. Lakshminarayanan ◽

Z. Cheng ◽

M.R. Bowers ◽

...

Keyword(s):

Machine Learning ◽

Head And Neck Cancer ◽

Head And Neck ◽

Salivary Glands ◽

Cancer Patients ◽

Neck Cancer ◽

Learning Methods ◽

Machine Learning Methods

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Machine learning methods applied to audit of surgical margins after curative surgery for head and neck cancer

British Journal of Oral and Maxillofacial Surgery ◽

10.1016/j.bjoms.2020.08.041 ◽

2020 ◽

Author(s):

D. Tighe ◽

F. Fabris ◽

A. Freitas

Keyword(s):

Machine Learning ◽

Head And Neck Cancer ◽

Head And Neck ◽

Neck Cancer ◽

Surgical Margins ◽

Curative Surgery ◽

Learning Methods ◽

Machine Learning Methods

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Machine Learning Methods Uncover Radiomorphologic Dose Patterns in Salivary Glands that Predict Xerostomia in Patients with Head and Neck Cancer

Advances in Radiation Oncology ◽

10.1016/j.adro.2018.11.008 ◽

2019 ◽

Vol 4 (2) ◽

pp. 401-412 ◽

Author(s):

Wei Jiang ◽

Pranav Lakshminarayanan ◽

Xuan Hui ◽

Peijin Han ◽

Zhi Cheng ◽

...

Keyword(s):

Machine Learning ◽

Head And Neck Cancer ◽

Head And Neck ◽

Salivary Glands ◽

Neck Cancer ◽

Learning Methods ◽

Machine Learning Methods

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61: Conventional and Machine Learning Analyses to Differentiate Systematic Versus Random Inter-Fractional Changes in a Cohort of 250 Head and Neck Cancer Patients

Radiotherapy and Oncology ◽

10.1016/s0167-8140(21)08894-0 ◽

2021 ◽

Vol 163 ◽

pp. S75

Author(s):

Nabhya Harjai ◽

Sarah Weppler ◽

Craig A. Beers ◽

Lukas V. Dyke ◽

Colleen Schinkel ◽

...

Keyword(s):

Machine Learning ◽

Head And Neck Cancer ◽

Head And Neck ◽

Cancer Patients ◽

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Effect of machine learning re-sampling techniques for imbalanced datasets in 18F-FDG PET-based radiomics model on prognostication performance in cohorts of head and neck cancer patients

European Journal of Nuclear Medicine and Molecular Imaging ◽

10.1007/s00259-020-04756-4 ◽

2020 ◽

Vol 47 (12) ◽

pp. 2826-2835 ◽

Author(s):

Chenyi Xie ◽

Richard Du ◽

Joshua WK Ho ◽

Herbert H Pang ◽

Keith WH Chiu ◽

...

Keyword(s):

Machine Learning ◽

Head And Neck Cancer ◽

Head And Neck ◽

Cancer Patients ◽

Neck Cancer ◽

Fdg Pet ◽

Sampling Techniques ◽

Imbalanced Datasets ◽

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Use of Machine Learning to Differentiate Residual Tumor from Radiation Changes in Head and Neck Cancer Patients Treated with Definitive Chemoradiotherapy

International Journal of Radiation Oncology*Biology*Physics ◽

10.1016/j.ijrobp.2020.02.621 ◽

2020 ◽

Vol 108 (2) ◽

pp. E63-E64

Author(s):

Toms Vengaloor Thomas ◽

Edward Florez ◽

Seth Lirette ◽

Ali Fatemi-Ardekani

Keyword(s):

Machine Learning ◽

Head And Neck Cancer ◽

Head And Neck ◽

Cancer Patients ◽

Neck Cancer ◽

Residual Tumor ◽

Definitive Chemoradiotherapy

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61: Conventional and Machine Learning Analyses to Differentiate Systematic Versus Random Inter-Fractional Changes in a Cohort of 250 Head and Neck Cancer Patients

Radiotherapy and Oncology ◽

10.1016/s0167-8140(20)30953-1 ◽

2020 ◽

Vol 150 ◽

pp. S29

Author(s):

Sarah Weppler ◽

Craig A. Beers ◽

Lukas V. Dyke ◽

Colleen Schinkel ◽

Wendy Smith ◽

...

Keyword(s):

Machine Learning ◽

Head And Neck Cancer ◽

Head And Neck ◽

Cancer Patients ◽

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Erratum to: Reddy JP, Lindsay WD, Berlind CG, Ahern CA, Holmes A, Smith BD, Phan J, Frank SJ, Gunn GB, Rosenthal DI, Morrison WH, Garden AS, Chronowski GM, Shah SJ, Mayo LL, and Fuller CD. Applying a Machine Learning Approach to Predict Acute Radiation Toxicities for Head and Neck Cancer Patients. Int J Radiat Oncol Biol Phys 2019;105(suppl 1):S69.

International Journal of Radiation Oncology*Biology*Physics ◽

10.1016/j.ijrobp.2019.10.015 ◽

2020 ◽

Vol 106 (1) ◽

pp. 223

Keyword(s):

Machine Learning ◽

Head And Neck Cancer ◽

Head And Neck ◽

Cancer Patients ◽

Neck Cancer ◽

Radiat Oncol Biol Phys ◽

Acute Radiation ◽

Learning Approach ◽

Machine Learning Approach

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Clustering of Largely Right-Censored Oropharyngeal Head and Neck Cancer Patients for Discriminative Groupings to Improve Outcome Prediction

Scientific Reports ◽

10.1038/s41598-020-60140-0 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Joel Tosado ◽

Luka Zdilar ◽

Hesham Elhalawani ◽

Baher Elgohari ◽

David M. Vock ◽

...

Keyword(s):

Head And Neck Cancer ◽

Head And Neck ◽

Cancer Patients ◽

Neck Cancer ◽

Outcome Prediction ◽

Improve Outcome

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PO-1764: Prognostic outcome prediction for head and neck cancer patients using convolutional neural networks

Radiotherapy and Oncology ◽

10.1016/s0167-8140(21)01782-5 ◽

2020 ◽

Vol 152 ◽

pp. S982

Author(s):

J. Guo ◽

T. Zhai ◽

R.J.H.M Steenbakkers ◽

S. Both ◽

J.A. Langendijk ◽

...

Keyword(s):

Neural Networks ◽

Head And Neck Cancer ◽

Head And Neck ◽

Cancer Patients ◽

Convolutional Neural Networks ◽

Neck Cancer ◽

Outcome Prediction ◽

Prognostic Outcome

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