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Thomas Fuchs

  1. "Medical Physics"
Formats
  1. Journal Article (18)
  2. Conference Paper (6)
  3. Meeting Abstract (3)
  4. Book Section (1)
  5. Research Letter (1)
Groups
  1. Medical Physics (29)
  2. Department of Pathology and Laboratory Medicine (18)
  3. Sloan Kettering Institute Postdocs (15)
  4. MSK Grad Students (12)
  5. Center for Pancreatic Cancer Research (9)
  6. DigITs Research Group (4)

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People
  1. Peter Schueffler (9)
  2. Chad Vanderbilt (7)
  3. Gabriele Campanella (7)
  4. David Klimstra (5)
  5. Dig Vijay Kumar Yarlagadda (5)
  6. Matthew Hanna (5)

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Years
  1. 2025 (1)
  2. 2022 (2)
  3. 2021 (6)
  4. 2020 (5)
  5. 2019 (5)
  6. 2018 (4)

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Publications
  1. Modern Pathology (5)
  2. Lecture Notes in Computer Science (4)
  3. Computerized Medical Imaging and Graphics (3)
  4. Journal of Pathology Informatics (2)
  5. Proceedings of Machine Learning Research (2)
  6. Academic Radiology (1)

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Publishers
  1. Nature Research (5)
  2. Springer (5)
  3. Nature Publishing Group (4)
  4. Elsevier Inc. (3)
  5. Elsevier Science, Inc. (3)
  6. Journal Machine Learning Research (2)

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Results (29)

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  • Independent validation of paige prostate: Assessing clinical benefit of an artificial intelligence tool within a digital diagnostic pathology laboratory workflow
    Meeting Abstract

    Kanan, C.; Sue, J.; Grady, L.; Fuchs, T. J.; Chandarlapaty, S.; Reis-Filho, J. S.; Salles, P. G. O.; da Silva, L. M.; Ferreira, C. G.; Pereira, E. M.
    Journal of Clinical Oncology (2020)

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  • Interpretable multimodal deep learning for real-time pan-tissue pan-disease pathology search on social media
    Journal Article

    Schaumberg, A. J.; Juarez-Nicanor, W. C.; Choudhury, S. J.; Pastrián, L. G.; Pritt, B. S.; Prieto Pozuelo, M.; Sotillo Sánchez, R.; Ho, K.; Zahra, N.; Sener, B. D.; more...
    Modern Pathology (2020)

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  • Deep interactive learning: An efficient labeling approach for deep learning-based osteosarcoma treatment response assessment
    Conference Paper

    Ho, D. J.; Agaram, N. P.; Schüffler, P. J.; Vanderbilt, C. M.; Jean, M. H.; Hameed, M. R.; Fuchs, T. J.
    Springer (2020)

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  • Novel artificial intelligence system increases the detection of prostate cancer in whole slide images of core needle biopsies
    Journal Article

    Raciti, P.; Sue, J.; Ceballos, R.; Godrich, R.; Kunz, J. D.; Kapur, S.; Reuter, V.; Grady, L.; Kanan, C.; Klimstra, D. S.; more...
    Modern Pathology (2020)

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  • VOCA: Cell nuclei detection in histopathology images by vector oriented confidence accumulation
    Conference Paper

    Xie, C.; Vanderbilt, C. M.; Grabenstetter, A.; Fuchs, T. J.
    Journal Machine Learning Research (2019)

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  • Unsupervised subtyping of cholangiocarcinoma using a deep clustering convolutional autoencoder
    Conference Paper

    Muhammad, H.; Sigel, C. S.; Campanella, G.; Boerner, T.; Pak, L. M.; Büttner, S.; Ijzermans, J. N. M.; Koerkamp, B. G.; Doukas, M.; Jarnagin, W. R.; more...
    Springer (2019)

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  • Clinical-grade computational pathology using weakly supervised deep learning on whole slide images
    Journal Article

    Campanella, G.; Hanna, M. G.; Geneslaw, L.; Miraflor, A.; Werneck Krauss Silva, V.; Busam, K. J.; Brogi, E.; Reuter, V. E.; Klimstra, D. S.; Fuchs, T. J.
    Nature Medicine (2019)

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  • Whole slide imaging equivalency and efficiency study: Experience at a large academic center
    Journal Article

    Hanna, M. G.; Reuter, V. E.; Hameed, M. R.; Tan, L. K.; Chiang, S.; Sigel, C.; Hollmann, T.; Giri, D.; Samboy, J.; Moradel, C.; more...
    Modern Pathology (2019)

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  • DeepPET: A deep encoder-decoder network for directly solving the PET image reconstruction inverse problem
    Journal Article

    Häggström, I.; Schmidtlein, C. R.; Campanella, G.; Fuchs, T. J.
    Medical Image Analysis (2019)

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  • Survival modeling of pancreatic cancer with radiology using convolutional neural networks
    Conference Paper

    Muhammad, H.; Häggström, I.; Klimstra, D. S.; Fuchs, T. J.
    Springer (2018)

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