Machine Learning Applications in Head and Neck Radiation Oncology: Lessons From Open-Source Radiomics Challenges

Hesham Elhalawani, Timothy A. Lin, Stefania Volpe, Abdallah S. R. Mohamed, Aubrey L. White, James Zafereo, Andrew J. Wong, Joel E. Berends, Shady AboHashem, Bowman Williams, Jeremy M. Aymard, Aasheesh Kanwar, Subha Perni, Crosby D. Rock, Luke Cooksey, Shauna Campbell, Pei Yang, Khahn Nguyen, Rachel B. Ger, Carlos E. Cardenas, Xenia J. Fave, Carlo Sansone, Gabriele Piantadosi, Stefano Marrone, Rongjie Liu, Chao Huang, Kaixian Yu, Tengfei Li, Yang Yu, Youyi Zhang, Hongtu Zhu, Jeffrey S. Morris, Veerabhadran Baladandayuthapani, John W. Shumway, Alakonanda Ghosh, Andrei Pöhlmann, Hady A. Phoulady, Vibhas Goyal, Guadalupe Canahuate, G. Elisabeta Marai, David Vock, Stephen Y. Lai, Dennis S. Mackin, Laurence E. Court, John Freymann, Keyvan Farahani, Jayashree Kaplathy-Cramer, Clifton D. Fuller

Open source

DOI: 10.3389/fonc.2018.00294
Published: 2018-08-17
Container: Frontiers in Oncology
Publisher: Frontiers Media SA
Open access: unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

supportingDOI registered: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
supportingDOI resolves: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.3389/fonc.2018.00294,
  title = {Machine Learning Applications in Head and Neck Radiation Oncology: Lessons From Open-Source Radiomics Challenges},
  author = {Hesham Elhalawani and Timothy A. Lin and Stefania Volpe and Abdallah S. R. Mohamed and Aubrey L. White and James Zafereo and Andrew J. Wong and Joel E. Berends and Shady AboHashem and Bowman Williams and Jeremy M. Aymard and Aasheesh Kanwar and Subha Perni and Crosby D. Rock and Luke Cooksey and Shauna Campbell and Pei Yang and Khahn Nguyen and Rachel B. Ger and Carlos E. Cardenas and Xenia J. Fave and Carlo Sansone and Gabriele Piantadosi and Stefano Marrone and Rongjie Liu and Chao Huang and Kaixian Yu and Tengfei Li and Yang Yu and Youyi Zhang and Hongtu Zhu and Jeffrey S. Morris and Veerabhadran Baladandayuthapani and John W. Shumway and Alakonanda Ghosh and Andrei Pöhlmann and Hady A. Phoulady and Vibhas Goyal and Guadalupe Canahuate and G. Elisabeta Marai and David Vock and Stephen Y. Lai and Dennis S. Mackin and Laurence E. Court and John Freymann and Keyvan Farahani and Jayashree Kaplathy-Cramer and Clifton D. Fuller},
  year = {2018},
  journal = {Frontiers in Oncology},
  doi = {10.3389/fonc.2018.00294},
  url = {https://doi.org/10.3389/fonc.2018.00294}
}

RIS

TY  - JOUR
TI  - Machine Learning Applications in Head and Neck Radiation Oncology: Lessons From Open-Source Radiomics Challenges
AU  - Hesham Elhalawani
AU  - Timothy A. Lin
AU  - Stefania Volpe
AU  - Abdallah S. R. Mohamed
AU  - Aubrey L. White
AU  - James Zafereo
AU  - Andrew J. Wong
AU  - Joel E. Berends
AU  - Shady AboHashem
AU  - Bowman Williams
AU  - Jeremy M. Aymard
AU  - Aasheesh Kanwar
AU  - Subha Perni
AU  - Crosby D. Rock
AU  - Luke Cooksey
AU  - Shauna Campbell
AU  - Pei Yang
AU  - Khahn Nguyen
AU  - Rachel B. Ger
AU  - Carlos E. Cardenas
AU  - Xenia J. Fave
AU  - Carlo Sansone
AU  - Gabriele Piantadosi
AU  - Stefano Marrone
AU  - Rongjie Liu
AU  - Chao Huang
AU  - Kaixian Yu
AU  - Tengfei Li
AU  - Yang Yu
AU  - Youyi Zhang
AU  - Hongtu Zhu
AU  - Jeffrey S. Morris
AU  - Veerabhadran Baladandayuthapani
AU  - John W. Shumway
AU  - Alakonanda Ghosh
AU  - Andrei Pöhlmann
AU  - Hady A. Phoulady
AU  - Vibhas Goyal
AU  - Guadalupe Canahuate
AU  - G. Elisabeta Marai
AU  - David Vock
AU  - Stephen Y. Lai
AU  - Dennis S. Mackin
AU  - Laurence E. Court
AU  - John Freymann
AU  - Keyvan Farahani
AU  - Jayashree Kaplathy-Cramer
AU  - Clifton D. Fuller
PY  - 2018
JO  - Frontiers in Oncology
DO  - 10.3389/fonc.2018.00294
UR  - https://doi.org/10.3389/fonc.2018.00294
ER  -

APA

Elhalawani, H., Lin, T. A., Volpe, S., Mohamed, A. S. R., White, A. L., Zafereo, J., Wong, A. J., Berends, J. E., AboHashem, S., Williams, B., Aymard, J. M., Kanwar, A., Perni, S., Rock, C. D., Cooksey, L., Campbell, S., Yang, P., Nguyen, K., Ger, R. B., Cardenas, C. E., Fave, X. J., Sansone, C., Piantadosi, G., Marrone, S., Liu, R., Huang, C., Yu, K., Li, T., Yu, Y., Zhang, Y., Zhu, H., Morris, J. S., Baladandayuthapani, V., Shumway, J. W., Ghosh, A., Pöhlmann, A., Phoulady, H. A., Goyal, V., Canahuate, G., Marai, G. E., Vock, D., Lai, S. Y., Mackin, D. S., Court, L. E., Freymann, J., Farahani, K., Kaplathy-Cramer, J., & Fuller, C. D. (2018). Machine Learning Applications in Head and Neck Radiation Oncology: Lessons From Open-Source Radiomics Challenges. Frontiers in Oncology. https://doi.org/10.3389/fonc.2018.00294

Source records

crossref · retrieved 2026-09-25T14:48:31.584Z