Patel, H, Zanos, T, Hewitt, DB (January 2024) Deep Learning Applications in Pancreatic Cancer. Cancers, 16 (2). p. 436. ISSN 2072-6694
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Abstract
Pancreatic cancer is one of the most lethal gastrointestinal malignancies. Despite advances in cross-sectional imaging, chemotherapy, radiation therapy, and surgical techniques, the 5-year overall survival is only 12%. With the advent and rapid adoption of AI across all industries, we present a review of applications of DL in the care of patients diagnosed with PC. A review of different DL techniques with applications across diagnosis, management, and monitoring is presented across the different pathological subtypes of pancreatic cancer. This systematic review highlights AI as an emerging technology in the care of patients with pancreatic cancer.
Item Type: | Paper |
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Subjects: | bioinformatics diseases & disorders > cancer diseases & disorders bioinformatics > computational biology > algorithms bioinformatics > computational biology bioinformatics > computational biology > algorithms > machine learning diseases & disorders > cancer > cancer types > pancreatic cancer diseases & disorders > cancer > cancer types |
CSHL Authors: | |
Communities: | CSHL labs > Dos Santos lab |
SWORD Depositor: | CSHL Elements |
Depositing User: | CSHL Elements |
Date: | 1 January 2024 |
Date Deposited: | 08 Feb 2024 13:35 |
Last Modified: | 08 Feb 2024 13:35 |
Related URLs: | |
URI: | https://repository.cshl.edu/id/eprint/41431 |
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