• 4754 Citations
  • 12 h-Index
20022019

Research output per year

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Research Output

Deep learning convolutional neural networks for the estimation of liver fibrosis severity from ultrasound texture

Treacher, A., Beauchamp, D., Quadri, B., Fetzer, D., Vij, A., Yokoo, T. & Montillo, A., Jan 1 2019, Medical Imaging 2019: Computer-Aided Diagnosis. Mori, K. & Hahn, H. K. (eds.). SPIE, 109503E. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; vol. 10950).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Multiple deep learning architectures achieve superior performance diagnosing autism spectrum disorder using features previously extracted from structural and functional mri

    Mellema, C., Treacher, A., Nguyen, K. & Montillo, A., Apr 2019, ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging. IEEE Computer Society, p. 1891-1895 5 p. 8759193. (Proceedings - International Symposium on Biomedical Imaging; vol. 2019-April).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Predicting response to the antidepressant bupropion using pretreatment fMRI

    Nguyen, K. P., Fatt, C. C., Treacher, A., Mellema, C., Trivedi, M. H. & Montillo, A., Jan 1 2019, Predictive Intelligence in Medicine - 2nd International Workshop, PRIME 2019, Held in Conjunction with MICCAI 2019, Proceedings. Rekik, I., Adeli, E. & Park, S. H. (eds.). Springer, p. 53-62 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11843 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Sensitivity of derived clinical biomarkers to rs-fmri preprocessing software versions

    Nguyen, K. P., Fatt, C. C., Mellema, C., Trivedi, M. H. & Montillo, A., Apr 2019, ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging. IEEE Computer Society, p. 1581-1584 4 p. 8759526. (Proceedings - International Symposium on Biomedical Imaging; vol. 2019-April).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Determining the optimal number of MEG trials: A machine learning and speech decoding perspective

    Dash, D., Ferrari, P., Malik, S., Montillo, A., Maldjian, J. A. & Wang, J., Jan 1 2018, Brain Informatics - International Conference, BI 2018, Proceedings. Yang, Y., Yamamoto, V., Wang, S., Jones, E., Su, J., Mitchell, T. & Iasemidis, L. (eds.). Springer Verlag, p. 163-172 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11309 LNAI).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • 6 Scopus citations