Publication

Deep learning-aided decision support for diagnosis of skin disease across skin tones

Groh, M., Badri, O., Daneshjou, R. et al. Deep learning-aided decision support for diagnosis of skin disease across skin tones. Nat Med (2024). https://doi.org/10.1038/s41591-023-02728-3

Publication

Magnetomicrometry

C. R. Taylor, S. S. Srinivasan, S. H. Yeon, M. K. O'Donnell, T. J. Roberts, H. M. Herr, Magnetomicrometry, Sci.Robot. 6, eabg0656 (2021), DOI: 10.1126/scirobotics.abg0656

Publication

Experimentally Verified Finite Element Modeling and Analysis of a Conformable Piezoelectric Sensor

Amiri, N., Tasnim, F., Tavakkoli Anbarani, M., Dagdeviren, C.†, Karami, A.†, “Experimentally Verified Finite Element Modeling and Analysis of a Conformable Piezoelectric Sensor”, Smart Materials and Structures, 30 085017, 2021.

Publication

Automated end-to-end deep learning framework for classification and tumor localization from native nonstained pathology images

Akram Bayat, Connor Anderson and Pratik Shah. "Automated end-to-end deep learning framework for classification and tumor localization from native nonstained pathology images," Proc. SPIE 11596, Medical Imaging 2021: Image Processing, 115960A (15 February 2021); doi: 10.1117/12.2582303

Publication

Decoding of Facial Strains via Conformable Piezoelectric Interfaces

Sun, T.*, Tasnim, F.*, McIntosh, R. T., Amiri, N., Solav, D., Anbarani, M. T., Sadat, S., Zhang, L., Gu, Y., Karami, M. A., Dagdeviren, C.†, “Decoding of Facial Strains via Conformable Piezoelectric Interfaces”, Nature Biomedical Engineering, 4, 954–972, 2020.

Publication

Magnetomicrometry: Tissue Length Tracking via Implanted Magnetic Beads

C. Taylor, Magnetomicrometry : Tissue length tracking via implanted magnetic beads (2020). https://dspace.mit.edu/handle/1721.1/130210

Publication

Low-latency tracking of multiple permanent magnets

C. R. Taylor, H. G. Abramson, and H. M. Herr, “Low-Latency Tracking of Multiple Permanent Magnets,” IEEE Sensors Journal, pp. 1–11, 2019.

Publication

Adversarial attacks on medical machine learning

Finlayson, S. G., Bowers, J. D., Ito, J., Zittrain, J. L., Beam, A. L., & Kohane, I. S. (2019). Adversarial attacks on medical machine learning. Science, 363(6433), 1287. https://doi.org/10.1126/science.aaw4399

Publication

Computational histological staining and destaining of prostate core biopsy RGB images with generative adversarial neural networks

Aman Rana, Yauney G, Lowe A, Shah P. IEEE Xplore, Proceedings of 17th International Conference on Machine Learning and Applications (2018) (Conference acceptance rate: 14%). DOI: 10.1109/ICMLA.2018.00133

Publication

Machine learning algorithms for classification of microcirculation images from septic and non-septic patients

Perikumar Javia, Rana A, Shapiro NI, Shah P. IEEE Xplore, Proceedings of 17th International Conference on Machine Learning and Applications (2018) (Conference acceptance rate: 14%). DOI: 10.1109/ICMLA.2018.00097