NCI's Office of Data Sharing Annual Symposium (Abstract Submission): Submission #5
Submission information
Submission Number: 5
Submission ID: 144474
Submission UUID: e3560a33-19a5-4a72-8d5c-b8cf70c1a657
Submission URI: /ods/annualdatasharingsymposium/abstract
Submission Update: /ods/annualdatasharingsymposium/abstract?token=HmEmJFE3sC_0fb1VqT6Ztj24PqpwQ7XPkdrLNDXcwNw
Created: Wed, 06/11/2025 - 12:31
Completed: Wed, 06/11/2025 - 13:17
Changed: Thu, 06/12/2025 - 01:07
Remote IP address: 10.208.28.229
Submitted by: Anonymous
Language: English
Is draft: No
First Name | Julia |
---|---|
Middle Initial | |
Last Name | Komissarchik |
Degree(s) | MS |
Position/Title/Career Status | CEO & co-founder |
Organization | Glendor, Inc |
Organization Address | Draper |
julia@glendor.com | |
Abstract Category | Demo Table Request |
Abstract Keywords | multimodal data, PHI De-identification, patient's privacy, privacy protection, BAA-free data sharing |
Abstract Title | Automatic at source scalable removal of PHI from multimodal medical data to empower data sharing, while protecting patient's privacy. |
Abstract Summary | The rapid expansion of data in cancer research includes a wealth of multimodal datasets such as medical images, pathology slides, surgical videos, photos, and audio recordings. As researchers begin to collect, aggregate, and analyze this diverse range of data, protecting patient privacy and ensuring highly scalable de-identification of Protected Health Information (PHI) for all kinds of medical data becomes critical. This poster describes Glendor PHI Sanitizer - software for automatic at source scalable removal of PHI from multimodal medical data to empower data sharing, while protecting patient's privacy. |
Upload Abstract |
Glendor Poster.pdf2.22 MB
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