Predicting a Diagnostic Test Result From Patient Laboratory Testing History
The present disclosure relates to techniques for preprocessing samples and using preprocessed samples and machine learning models to predict clinical diagnostic tests for a patient from their historical laboratory testing data. Particularly, aspects are directed to obtaining datasets including featu...
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| Format | Patent |
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| Language | English |
| Published |
14.11.2022
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| Online Access | Get full text |
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| Summary: | The present disclosure relates to techniques for preprocessing samples and using preprocessed samples and machine learning models to predict clinical diagnostic tests for a patient from their historical laboratory testing data. Particularly, aspects are directed to obtaining datasets including features and/or historical laboratory test results for subjects, filtering the datasets based on a denoise-balance scheme to obtain filtered datasets, training a machine learning model using the filtered datasets to obtain a trained machine learning model, and providing the trained machine learning model. A candidate machine learning model may be an ensemble of classifiers implemented with a boosting algorithm, and the ensemble is trained by applying base machine learning algorithms on different distributions of the filtered datasets. The ensemble is then combined into a machine learning model having the set of learned model parameters for predicting results for clinical diagnostic tests. |
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