Despite considerable research efforts, pancreatic cancer is associated with a dire prognosis and a 5-year survival rate of only 10%. Early symptoms of the disease are mostly nonspecific. The premise of improved survival through early detection is tha...
PURPOSE: The application of Cox proportional hazards (CoxPH) models to survival data and the derivation of hazard ratio (HR) are well established. Although nonlinear, tree-based machine learning (ML) models have been developed and applied to the surv...
Journal of the American Medical Informatics Association : JAMIA
Mar 1, 2021
OBJECTIVE: Like most real-world data, electronic health record (EHR)-derived data from oncology patients typically exhibits wide interpatient variability in terms of available data elements. This interpatient variability leads to missing data and can...
Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]
Jan 6, 2021
Traditional survival methods have a wide application in the field of biomedical research. However, applying traditional survival methods requires data to meet a set of special assumptions while the Random Survival Forest model can overcome this incon...
BACKGROUND AND AIMS: Standardized and robust risk-stratification systems for patients with hepatocellular carcinoma (HCC) are required to improve therapeutic strategies and investigate the benefits of adjuvant systemic therapies after curative resect...
Studies in health technology and informatics
Sep 4, 2020
The current pandemic can likely have several waves and will require a major effort to save lives and provide optimal treatment. The efficient clinical resource planning and efficient treatment require identification of risk groups and specific clinic...
MOTIVATION: Recent advances in deep learning have offered solutions to many biomedical tasks. However, there remains a challenge in applying deep learning to survival analysis using human cancer transcriptome data. As the number of genes, the input v...
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