Clinical prediction models using machine learning in oncology: challenges and recommendations

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• Calculating the sample size required for developing a clinical prediction model

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• Evaluation of clinical prediction models (part 1): from development to external validation

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• The harm of class imbalance corrections for risk prediction models: illustration and simulation using logistic regression

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• Evaluation of clinical prediction models (part 3): calculating the sample size required for an external validation study

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• Methodological conduct of prognostic prediction models developed using machine learning in oncology: a systematic review

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• Reporting of prognostic clinical prediction models based on machine learning methods in oncology needs to be improved

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• Validation of prediction models in the presence of competing risks: a guide through modern methods

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• Risk of bias of prognostic models developed using machine learning: a systematic review in oncology

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• Overinterpretation of findings in machine learning prediction model studies in oncology: a systematic review

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• Adaptive sample size determination for the development of clinical prediction models

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• Larger sample sizes are needed when developing a clinical prediction model using machine learning in oncology: methodological systematic review

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• Guidance for unbiased predictive information for healthcare decision-making and equity (GUIDE): considerations when race may be a prognostic factor

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• Statistical models versus machine learning for competing risks: development and validation of prognostic models

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14 results