Machine learning and modeling: Data, validation, communication challenges

Issam El Naqa*, Dan Ruan, Gilmer Valdes, Andre Dekker, Todd McNutt, Yaorong Ge, Q. Jackie Wu, Jung Hun Oh, Maria Thor, Wade Smith, Arvind Rao, Clifton Fuller, Ying Xiao, Frank Manion, Matthew Schipper, Charles Mayo, Jean M. Moran, Randall Ten Haken

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Original languageEnglish
Pages (from-to)E834-E840
Number of pages7
JournalMedical Physics
Volume45
Issue number10
DOIs
Publication statusPublished - Oct 2018

Keywords

  • big data
  • machine learning
  • radiation oncology
  • ARTIFICIAL NEURAL-NETWORKS
  • RADIATION-THERAPY OUTCOMES
  • CELL LUNG-CANCER
  • IMRT PLANS
  • ROC CURVE
  • PREDICTION
  • RADIOTHERAPY
  • PNEUMONITIS
  • AREA
  • ALGORITHMS

Cite this

El Naqa, I., Ruan, D., Valdes, G., Dekker, A., McNutt, T., Ge, Y., ... Ten Haken, R. (2018). Machine learning and modeling: Data, validation, communication challenges. Medical Physics, 45(10), E834-E840. https://doi.org/10.1002/mp.12811
El Naqa, Issam ; Ruan, Dan ; Valdes, Gilmer ; Dekker, Andre ; McNutt, Todd ; Ge, Yaorong ; Wu, Q. Jackie ; Oh, Jung Hun ; Thor, Maria ; Smith, Wade ; Rao, Arvind ; Fuller, Clifton ; Xiao, Ying ; Manion, Frank ; Schipper, Matthew ; Mayo, Charles ; Moran, Jean M. ; Ten Haken, Randall. / Machine learning and modeling : Data, validation, communication challenges. In: Medical Physics. 2018 ; Vol. 45, No. 10. pp. E834-E840.
@article{24e56c462afe4b5183695c3287889825,
title = "Machine learning and modeling: Data, validation, communication challenges",
keywords = "big data, machine learning, radiation oncology, ARTIFICIAL NEURAL-NETWORKS, RADIATION-THERAPY OUTCOMES, CELL LUNG-CANCER, IMRT PLANS, ROC CURVE, PREDICTION, RADIOTHERAPY, PNEUMONITIS, AREA, ALGORITHMS",
author = "{El Naqa}, Issam and Dan Ruan and Gilmer Valdes and Andre Dekker and Todd McNutt and Yaorong Ge and Wu, {Q. Jackie} and Oh, {Jung Hun} and Maria Thor and Wade Smith and Arvind Rao and Clifton Fuller and Ying Xiao and Frank Manion and Matthew Schipper and Charles Mayo and Moran, {Jean M.} and {Ten Haken}, Randall",
year = "2018",
month = "10",
doi = "10.1002/mp.12811",
language = "English",
volume = "45",
pages = "E834--E840",
journal = "Medical Physics",
issn = "0094-2405",
publisher = "Wiley",
number = "10",

}

El Naqa, I, Ruan, D, Valdes, G, Dekker, A, McNutt, T, Ge, Y, Wu, QJ, Oh, JH, Thor, M, Smith, W, Rao, A, Fuller, C, Xiao, Y, Manion, F, Schipper, M, Mayo, C, Moran, JM & Ten Haken, R 2018, 'Machine learning and modeling: Data, validation, communication challenges', Medical Physics, vol. 45, no. 10, pp. E834-E840. https://doi.org/10.1002/mp.12811

Machine learning and modeling : Data, validation, communication challenges. / El Naqa, Issam; Ruan, Dan; Valdes, Gilmer; Dekker, Andre; McNutt, Todd; Ge, Yaorong; Wu, Q. Jackie; Oh, Jung Hun; Thor, Maria; Smith, Wade; Rao, Arvind; Fuller, Clifton; Xiao, Ying; Manion, Frank; Schipper, Matthew; Mayo, Charles; Moran, Jean M.; Ten Haken, Randall.

In: Medical Physics, Vol. 45, No. 10, 10.2018, p. E834-E840.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Machine learning and modeling

T2 - Data, validation, communication challenges

AU - El Naqa, Issam

AU - Ruan, Dan

AU - Valdes, Gilmer

AU - Dekker, Andre

AU - McNutt, Todd

AU - Ge, Yaorong

AU - Wu, Q. Jackie

AU - Oh, Jung Hun

AU - Thor, Maria

AU - Smith, Wade

AU - Rao, Arvind

AU - Fuller, Clifton

AU - Xiao, Ying

AU - Manion, Frank

AU - Schipper, Matthew

AU - Mayo, Charles

AU - Moran, Jean M.

AU - Ten Haken, Randall

PY - 2018/10

Y1 - 2018/10

KW - big data

KW - machine learning

KW - radiation oncology

KW - ARTIFICIAL NEURAL-NETWORKS

KW - RADIATION-THERAPY OUTCOMES

KW - CELL LUNG-CANCER

KW - IMRT PLANS

KW - ROC CURVE

KW - PREDICTION

KW - RADIOTHERAPY

KW - PNEUMONITIS

KW - AREA

KW - ALGORITHMS

U2 - 10.1002/mp.12811

DO - 10.1002/mp.12811

M3 - Article

VL - 45

SP - E834-E840

JO - Medical Physics

JF - Medical Physics

SN - 0094-2405

IS - 10

ER -