Evaluation of machine learning methods for the retrospective detection of ovarian cancer recurrences from chemotherapy data
Background: Cancer recurrences are poorly recorded within electronic health records around the world. This hinders research into the efficacy of cancer treatments. Currently, the retrospective identification of recurrence/progression diagnosis dates is achieved by staff who manually review patients’...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-06-01
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| Series: | ESMO Real World Data and Digital Oncology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S294982012400016X |
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