Publications [#352450] of Guillermo Sapiro

Papers Published

1. Asiedu, MN; Skerrett, E; Sapiro, G; Ramanujam, N, Combining multiple contrasts for improving machine learning-based classification of cervical cancers with a low-cost point-of-care Pocket colposcope., Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, vol. 2020 (July, 2020), pp. 1148-1151, ISBN 9781728119908
   (last updated on 2025/02/02)

   Abstract:
   We apply feature-extraction and machine learning methods to multiple sources of contrast (acetic acid, Lugol's iodine and green light) from the white Pocket Colposcope, a low-cost point of care colposcope for cervical cancer screening. We combine features from the sources of contrast and analyze diagnostic improvements with addition of each contrast. We find that overall AUC increases with additional contrast agents compared to using only one source.