• Hormesis Podcast #7 - Big Data: Headbutt your way into medicine...

  • 2020/02/08
  • 再生時間: 1 時間 2 分
  • ポッドキャスト

Hormesis Podcast #7 - Big Data: Headbutt your way into medicine...

  • サマリー

  • In this episode Sean and Nick lead our discussion of Big Data as it relates to Radiation Oncology medical physics. The discussion ranges from reasons to buy in, how we are starting to do it, and how we can proceed as a field in light of big data analytics.

    References:

    Matuszak, M. M., Fuller, C. D., Yock, T. I., Hess, C. B., McNutt, T., Jolly, S., Gabriel, P., Mayo, C. S., Thor, M., Caissie, A., Rao, A., Owen, D., Smith, W., Palta, J., Kapoor, R., Hayman, J., Waddle, M., Rosenstein, B., Miller, R., … Feng, M. (2018). Performance/outcomes data and physician process challenges for practical big data efforts in radiation oncology. Medical Physics, 45(10), e811–e819. https://doi.org/10.1002/mp.13136

    Mackie, T. R., Jackson, E. F., & Giger, M. (2018). Opportunities and challenges to utilization of quantitative imaging: Report of the AAPM practical big data workshop. Medical Physics, 45(10), e820–e828. https://doi.org/10.1002/mp.13135

    Mayo, C., Phillips, M., McNutt, T., Palta, J., Dekker, A., Miller, R., Xiao, Y., Moran, J., Matuszak, M., Gabriel, P., Ayan, A., Prisciandaro, J., Thor, M., Dixit, N., Popple, R., Killoran, J., Kaleba, E., Kantor, M., Ruan, D., … Lawrence, T. (2018). Treatment data and technical process challenges for practical big data efforts in radiation oncology. Medical Physics, 45(10), e793–e810. https://doi.org/10.1002/mp.13114

    McNutt, T. R., Bowers, M., Cheng, Z., Han, P., Hui, X., Moore, J., … Quon, H. (2018). Practical data collection and extraction for big data applications in radiotherapy. Medical Physics, 45(10), e863–e869. https://doi.org/10.1002/mp.12817

    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

    Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: promise and potential. Health Information Science and Systems, 2(1). https://doi.org/10.1186/2047-2501-2-3

    Spector-Bagdady, K., & Jagsi, R. (2018). Big data, ethics, and regulations: Implications for consent in the learning health system. Medical Physics, 45(10), e845–e847. https://doi.org/10.1002/mp.12707

    Traverso, A., van Soest, J., Wee, L., & Dekker, A. (2018). The radiation oncology ontology (ROO): Publishing linked data in radiation oncology using semantic web and ontology techniques. Medical Physics, 45(10), e854–e862. https://doi.org/10.1002/mp.12879

    Vikram, B. (2018). Perspectives on potential research benefits from big data efforts in Radiation Oncology. Medical Physics, 45(10), e848–e849. https://doi.org/10.1002/mp.13109

    Zou, W., Geng, H., Teo, B. K., Finlay, J., & Xiao, Y. (2018). NCTN clinical trial standardization for radiotherapy through IROC and CIRO. Medical Physics, 45(10), e850–e853. https://doi.org/10.1002/mp.12873

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あらすじ・解説

In this episode Sean and Nick lead our discussion of Big Data as it relates to Radiation Oncology medical physics. The discussion ranges from reasons to buy in, how we are starting to do it, and how we can proceed as a field in light of big data analytics.

References:

Matuszak, M. M., Fuller, C. D., Yock, T. I., Hess, C. B., McNutt, T., Jolly, S., Gabriel, P., Mayo, C. S., Thor, M., Caissie, A., Rao, A., Owen, D., Smith, W., Palta, J., Kapoor, R., Hayman, J., Waddle, M., Rosenstein, B., Miller, R., … Feng, M. (2018). Performance/outcomes data and physician process challenges for practical big data efforts in radiation oncology. Medical Physics, 45(10), e811–e819. https://doi.org/10.1002/mp.13136

Mackie, T. R., Jackson, E. F., & Giger, M. (2018). Opportunities and challenges to utilization of quantitative imaging: Report of the AAPM practical big data workshop. Medical Physics, 45(10), e820–e828. https://doi.org/10.1002/mp.13135

Mayo, C., Phillips, M., McNutt, T., Palta, J., Dekker, A., Miller, R., Xiao, Y., Moran, J., Matuszak, M., Gabriel, P., Ayan, A., Prisciandaro, J., Thor, M., Dixit, N., Popple, R., Killoran, J., Kaleba, E., Kantor, M., Ruan, D., … Lawrence, T. (2018). Treatment data and technical process challenges for practical big data efforts in radiation oncology. Medical Physics, 45(10), e793–e810. https://doi.org/10.1002/mp.13114

McNutt, T. R., Bowers, M., Cheng, Z., Han, P., Hui, X., Moore, J., … Quon, H. (2018). Practical data collection and extraction for big data applications in radiotherapy. Medical Physics, 45(10), e863–e869. https://doi.org/10.1002/mp.12817

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

Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: promise and potential. Health Information Science and Systems, 2(1). https://doi.org/10.1186/2047-2501-2-3

Spector-Bagdady, K., & Jagsi, R. (2018). Big data, ethics, and regulations: Implications for consent in the learning health system. Medical Physics, 45(10), e845–e847. https://doi.org/10.1002/mp.12707

Traverso, A., van Soest, J., Wee, L., & Dekker, A. (2018). The radiation oncology ontology (ROO): Publishing linked data in radiation oncology using semantic web and ontology techniques. Medical Physics, 45(10), e854–e862. https://doi.org/10.1002/mp.12879

Vikram, B. (2018). Perspectives on potential research benefits from big data efforts in Radiation Oncology. Medical Physics, 45(10), e848–e849. https://doi.org/10.1002/mp.13109

Zou, W., Geng, H., Teo, B. K., Finlay, J., & Xiao, Y. (2018). NCTN clinical trial standardization for radiotherapy through IROC and CIRO. Medical Physics, 45(10), e850–e853. https://doi.org/10.1002/mp.12873

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