Mitani, Akinori

Underspecification Presents Challenges for Credibility in Modern Machine Learning

D'Amour, A., Heller, K., Moldovan, D., Adlam, B., Alipanahi, B., Beutel, A., Chen, C., Deaton, J., Eisenstein, J., Hoffman, M. D., et al. (2020) · arXiv

Domain Adaptation and Few-Shot LearningAdversarial Robustness in Machine Learning

Cited by 398

Apolipoprotein E, Especially Apolipoprotein E4, Increases the Oligomerization of Amyloid β Peptide

Hashimoto, T., Serrano-Pozo, A., Hori, Y., Adams, K. W., Takeda, S., Banerji, A. O., Mitani, A., Joyner, D., Thyssen, D. H., Bacskai, B. J., et al. (2012) · The Journal of Neuroscience

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 294

Detection of anaemia from retinal fundus images via deep learning

Mitani, A., Huang, A., Venugopalan, S., Corrado, G. S., Peng, L., Webster, D. R., Hammel, N., Liu, Y., & Varadarajan, A. V. (2019) · Nature Biomedical Engineering

Retinal Imaging and AnalysisArtificial Intelligence in Healthcare

Cited by 230

Artificial intelligence predictive model for hormone therapy use in prostate cancer

Spratt, D. E., Tang, S., Sun, Y., Huang, H.-C., Chen, E., Mohamad, O., Armstrong, A. J., Tward, J. D., Nguyen, P. L., Lang, J. M., et al. (2023) · NEJM Evidence

Prostate Cancer Diagnosis and TreatmentRadiomics and Machine Learning in Medical Imaging

Cited by 153