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Using machine learning, general regression, and cox proportional hazards regression to predict the effectiveness of treatment in patients with breast cancer
The objective of this feasibility study is to introduce machine learning algorithms in the combination of general regression and cox proportional hazards regression to predicate the outcome of disease management. By using the delay in the receipt of adjuvant chemotherapy and SEER-Medicare databases...
Tallennettuna:
| Päätekijät: | , , |
|---|---|
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
American Medical Informatics Association
2006
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC1839432/ https://ncbi.nlm.nih.gov/pubmed/17238752 |
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