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AssigneeJanssen Research & Development, LLC
InventorsJennifer Seto Harper, Rajarshi Roychowdhury, Smita Mitra, Jeffrey John Headd
Estimating the term…
Disclosed herein are methods for training and deploying a predictive model for generating a prediction, e.g., patient eligibility for a CAR-T therapy. Datasets, such as open healthcare claims datasets, may be missing data. Missing data may hamper the ability to generate sufficient information needed for training a predictive model. Methods include leveraging comprehensive datasets, such as closed claims datasets, to create training examples for input into a machine learning algorithm. In various embodiments, the comprehensive dataset is modified to simulate the data missingness in the target dataset; then, the modified dataset is paired with the ground truth label derived from the comprehensive dataset to create training examples. In various embodiments, a comprehensive dataset is paired with a target dataset to create training examples. After training a predictive model on such examples, the model can be deployed to make predictions in the target dataset even in light of missing data.
1-29. (canceled)
A computer-implemented method comprising:
A non-transitory computer readable medium comprising instructions that, when executed by a processor, cause the processor to perform one or more operations for:
A method of training a machine learning model, comprising:
A computer-implemented method comprising:
Dependencies are inferred from the claim text.