Conference paper2025Published

Performance Evaluation of a Stacked Classifier for Predicting Treatment Response in Unresectable Colorectal Liver Metastases

Mane Piliposyan, Mohammad Hamghalam, Ramtin Mojtahedi, Jacob J. Peoples, Kaitlyn S. Kobayashi, E. Claire Bunker, Natalie Gangai, Yun Shin Chun, Richard K. G. Do, Christian Muise, Amber L. Simpson

Medical Imaging 2025: Computer-Aided Diagnosis, Proceedings of SPIE 13407, 134071P.

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This conference paper is recorded in Medical Imaging 2025: Computer-Aided Diagnosis (2025). This page consolidates verified bibliographic metadata and the external records or research artifacts listed here.

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Work type
Conference paper
Year
2025
Publication date
2025-04-04
Status
Published
Venue
Medical Imaging 2025: Computer-Aided Diagnosis
Publisher
SPIE
Volume
13407
Pages
397-406
Article
134071P
Last verified
2026-08-02

Research topics

  • colorectal liver metastases
  • treatment response
  • stacked classifier
  • machine learning

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Mane Piliposyan, Mohammad Hamghalam, Ramtin Mojtahedi, Jacob J. Peoples, Kaitlyn S. Kobayashi, E. Claire Bunker, Natalie Gangai, Yun Shin Chun, Richard K. G. Do, Christian Muise, and Amber L. Simpson. “Performance Evaluation of a Stacked Classifier for Predicting Treatment Response in Unresectable Colorectal Liver Metastases.” Medical Imaging 2025: Computer-Aided Diagnosis, Proceedings of SPIE 13407, 134071P. https://doi.org/10.1117/12.3048943

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@inproceedings{Piliposyan2025StackedClassifier,
  author = {Mane Piliposyan and Mohammad Hamghalam and Ramtin Mojtahedi and Jacob J. Peoples and Kaitlyn S. Kobayashi and E. Claire Bunker and Natalie Gangai and Yun Shin Chun and Richard K. G. Do and Christian Muise and Amber L. Simpson},
  title = {{Performance Evaluation of a Stacked Classifier for Predicting Treatment Response in Unresectable Colorectal Liver Metastases}},
  year = {2025},
  booktitle = {Medical Imaging 2025: Computer-Aided Diagnosis},
  volume = {13407},
  pages = {397-406},
  publisher = {SPIE},
  doi = {10.1117/12.3048943},
  url = {https://doi.org/10.1117/12.3048943}
}

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