SYNTHETICALLY GENERATED HEALTHCARE DOCUMENTS FOR CLASSIFIER TRAINING
A synthetic generation of healthcare documents for use in training a classifier is described herein. Initially, a multiplicity of electronic forms are received in memory of a host computing system and data extracted from a specific common field located in each of the forms. A statistical metric is then computed for the specific common field a value synthetically generated for the specific common field according to the computed statistical metric. Finally, the synthetically generated value is inserted into the specific common field of a training version of the electronic forms and the training version of the electronic forms persisted as part of a training data set for a classifier adapted to classify the multiplicity of electronic forms.
1 . A method for synthetically generating health care forms for use in training a health care form classifier, the method comprising:
receiving a multiplicity of electronic forms in memory of a host computing system;
extracting data from a specific common field located in each of the forms;
computing a statistical metric for the specific common field;
synthetically generating a value for the specific common field according to the computed statistical metric;
inserting the synthetically generated value into the specific common field of a training version of the electronic forms; and,
persisting the training version of the electronic forms as part of a training data set for a classifier adapted to classify the multiplicity of electronic forms.
2 . The method of claim 1 , wherein the electronic forms conform to an annotated template including an identification of the specific common field.
3 . The method of claim 1 , further comprising:
generating random noise; and,
modifying the synthetically generated value with the random noise.
4 . The method of claim 1 , wherein the computed statistical metric is a distribution of values for the specific common field.
5 . A data processing system adapted for synthetically generating health care forms for use in training a health care form classifier, the system comprising:
a host computing platform comprising one or more computers, each with memory and one or processing units including one or more processing cores; and,
a synthetic form generation module comprising computer program instructions enabled while executing in the memory of at least one of the processing units of the host computing platform to perform:
receiving a multiplicity of electronic forms in memory of a host computing system;
extracting data from a specific common field located in each of the forms;
computing a statistical metric for the specific common field;
synthetically generating a value for the specific common field according to the computed statistical metric;
inserting the synthetically generated value into the specific common field of a training version of the electronic forms; and,
persisting the training version of the electronic forms as part of a training data set for a classifier adapted to classify the multiplicity of electronic forms.
6 . The system of claim 5 , wherein the electronic forms conform to an annotated template including an identification of the specific common field.
7 . The system of claim 5 , wherein the program instructions further perform:
generating random noise; and,
modifying the synthetically generated value with the random noise.
8 . The system of claim 5 , wherein the computed statistical metric is a distribution of values for the specific common field.
9 . A computing device comprising a non-transitory computer readable storage medium having program instructions stored therein, the instructions being executable by at least one processing core of a processing unit to cause the processing unit to perform a method for synthetically generating health care forms for use in training a health care form classifier, the instructions performing:
receiving a multiplicity of electronic forms in memory of a host computing system;
extracting data from a specific common field located in each of the forms;
computing a statistical metric for the specific common field;
synthetically generating a value for the specific common field according to the computed statistical metric;
inserting the synthetically generated value into the specific common field of a training version of the electronic forms; and,
persisting the training version of the electronic forms as part of a training data set for a classifier adapted to classify the multiplicity of electronic forms.
10 . The device of claim 9 , wherein the electronic forms conform to an annotated template including an identification of the specific common field.
11 . The device of claim 9 , wherein the program instructions further perform:
generating random noise; and,
modifying the synthetically generated value with the random noise.
12 . The device of claim 9 , wherein the computed statistical metric is a distribution of values for the specific common field.