Automated Extraction of Imaging and Pathology Data From Diverse Prostate Cancer Electronic Records
We developed an NLP algorithm and validated that it successfully captures salient information about data elements of interest in PCa research. Reliable extraction of these key data elements will have numerous uses for downstream research in this field.
Authors
- Grace Lee (ORCID: https://orcid.org/0000-0003-3638-1573)
- Daniel Chen (ORCID: https://orcid.org/0000-0001-6672-6814)
- Nhan Do (ORCID: https://orcid.org/0000-0001-6868-7011)
- John Bihn (ORCID: https://orcid.org/0000-0001-8029-8991)
- Karlynn E. Neu (ORCID: https://orcid.org/0000-0002-3481-813X)
- Oleg Soloviev (ORCID: https://orcid.org/0000-0003-3761-9192)
- Robert Zwolinski (ORCID: https://orcid.org/0000-0003-3466-6145)
- Nathanael R. Fillmore (ORCID: https://orcid.org/0000-0002-8058-3423)
- Sergey Goryachev
- Matthew R. Cooperberg (ORCID: https://orcid.org/0000-0003-4339-6685)
- Channing Judith Paller (ORCID: https://orcid.org/0000-0003-3658-1858)
- John Culnan
Institutions
- Boston University (US)
- San Francisco VA Medical Center (US)
- Harvard University (US)
- Johns Hopkins University (US)
- VA Boston Healthcare System (US)
- Department of Veterans Affairs (AU)
- UCSF Helen Diller Family Comprehensive Cancer Center (US)
Publication Details
- Journal
- JCO Clinical Cancer Informatics
- Published
- 2025-08-01
- DOI
- https://doi.org/10.1200/cci-25-00085
- Citations
- 3
- Primary Topic
- Prostate Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 4.56