Comments (2)
puckybreg
commented on August 23, 2024
Also interested in calculating the hazard beta parameters for the fit model. @alexxiecan I have yet to find anything in the examples or in the code itself that points to the best way to get the covariate effects on the Survival Curve.
For that matter, it seems that PyCox is mostly geared towards prediction and not explanation of the Survival Curve. Am I right in understanding that after fitting the model, there is no clear way to getting at the computed Kaplan-Meir curve beyond running model.predict on the test dataset?
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alexxiecan
commented on August 23, 2024
Firstly, I agree with you that the current deep survival model can only be used for prediction, and cannot calculate the hazard ratio or specific h (x) function values of certain variables like R language. But I guess if the data is sent to a trained model, its output should be the value of h (x)? I don't know if my understanding is correct? However, in terms of programming, I have not yet implemented....I hope we can continue to improve pycox and implement certain specific computing functions.
谢灿
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主题: Re: [havakv/pycox] about hazard value! (Issue #163)
Also interested in calculating the hazard beta parameters for the fit model. @alexxiecan I have yet to find anything in the examples or in the code itself that points to the best way to get the covariate effects on the Survival Curve.
For that matter, it seems that PyCox is mostly geared towards prediction and not explanation of the Survival Curve. Am I right in understanding that after fitting the model, there is no clear way to getting at the computed Kaplan-Meir curve beyond running model.predict on the test dataset?
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Related Issues (20)
- L1 and L2 penalty coxph HOT 1
- AssertionError： assert durations.shape[0] == surv.shape[1] == surv_idx.shape[0] == events.shape[0]
- METABRIC Covariates Subset HOT 1
- AttributeError: 'Series' object has no attribute 'is_monotonic' HOT 18
- Reproduction of the results in JMLR19 paper HOT 1
- Calculating Estimated Population Survival Curve HOT 4
- Some question about the result of deephit_competing_risks HOT 2
- AttributeError: 'DeepHitSingle' object has no attribute 'state_dict' HOT 1
- ValueError: cannot convert float NaN to integer HOT 1
- Softmax layer and residual connections in DeepHitSingle model HOT 1
- _initialization of _internal failed
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- A model to add
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- performance for ordinal categorical covariates
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