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- W4377092049 abstract "When patients with cancer develop depression, it is often left untreated. We developed a prediction model for depression risk within the first month after starting cancer treatment using machine learning and Natural Language Processing (NLP) models. The LASSO logistic regression model based on structured data performed well, whereas the NLP model based on only clinician notes did poorly. After further validation, prediction models for depression risk could lead to earlier identification and treatment of vulnerable patients, ultimately improving cancer care and treatment adherence." @default.
- W4377092049 created "2023-05-20" @default.
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- W4377092049 date "2023-05-18" @default.
- W4377092049 modified "2023-10-13" @default.
- W4377092049 title "Predicting Depression Risk in Patients with Cancer Using Multimodal Data" @default.
- W4377092049 doi "https://doi.org/10.3233/shti230274" @default.
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- W4377092049 hasPublicationYear "2023" @default.
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