System and method for determining an expression of an object
A system for determining an expression of an object. The system includes at least a processor and a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to determine an expression of an object. The instructions may include receive a first object, receive a second object, determine an expression of the first object in relation to the second object. Further, determining an expression of the first object in relation to the second object may include inputting the first object and the second object into an expression model, generating an expression, wherein the expression represents a relationship between the first object and the second object, outputting the expression representing the first object and the second object, and returning a value associated with the relationship between the first object and the second object.
1 . A system for determining an expression of an object, wherein the system comprises:
at least a processor; and
a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to:
receive a first object, wherein the first object comprises instances of a plurality of classes comprising one or more values and behaviors associated with patient data, wherein a class of the plurality of classes is generated using the at least a processor, wherein generating the class comprises:
defining the class, wherein defining the class comprises:
identifying one or more required criteria, wherein identifying the one or more required criteria comprises utilizing a parameter module;
selecting specific instances based on the one or more required criteria; and
instantiating the class using the specific instances based on the one or more required criteria;
verifying the class as a function of the specific instances associated with the class; and
displaying one or more objects of the class using a graphical user interface (GUI), wherein the GUI enables a user to adjust the class by adding instances, deleting instances, and adjusting instances, wherein the adjustment of the class further comprises an authorization process, wherein the authorization process comprises:
receiving, at the at least a processor, an adjustment signal:
generating a response signal as a function of the comparison of the adjustment signal, the class, and an optimization metric; and
transmitting the response signal to the GUI;
receive a second object, wherein:
the second object comprises instances of classes comprising one or more values and behaviors; and
the second object is generated by a machine-learning model using natural language processing to identify certain strings within a plurality of second object instances of classes; and
determine an expression of the first object in relation to the second object, wherein determining the expression of the first object in relation to the second object comprises:
inputting the first object and the second object into an expression model trained on historic patient data associated with historic payor data, wherein a large language model is implemented to parse unstructured data of the historic patient data, and wherein the at least a processor is configured to perform de-identification of personally identifiable information prior to training the expression model and re-identification after training the expression model in accordance with compliance protocols;
generating, at the expression model, the expression;
outputting the expression; and
returning a value associated with the expression.
2 . The system of claim 1 , wherein the second object further comprises one or more values and behaviors associated with one or more constraints generated from textual data.
3 . The system of claim 2 , wherein the one or more values and behaviors comprise historic data.
4 . The system of claim 1 , wherein the returned value comprises a set of values, wherein the set of values comprises a value vector comprising a plurality of temporally assigned values.
5 . The system of claim 1 , wherein the at least a processor is further configured to display, at a display device, the returned value associated with a relationship between the first object and the second object.
6 . The system of claim 5 , wherein the GUI comprises one or more event handlers.
7 . The system of claim 1 , wherein the at least a processor is further configured to transmit the returned value to a database.
8 . The system of claim 1 , wherein the first object and the second object are updated iteratively with newly occurring instances.
9 . The system of claim 8 , wherein the newly occurring instances are used as new training data to retrain the expression model.
10 . The system of claim 1 , wherein the expression model is trained using exemplary first and second objects correlated to exemplary expressions.
11 . A method for determining an expression of an object, wherein the method comprises:
receiving a first object, wherein the first object comprises instances of a plurality of classes comprising one or more values and behaviors associated with patient data, wherein a class of the plurality of classes is generated using the at least a processor, wherein generating the class comprises:
defining the class, wherein defining the class comprises:
identifying one or more required criteria, wherein identifying the one or more criteria comprises using a parameter module:
selecting specific instances based on the one or more required criteria; and
instantiating the class using the specific instances based on the one or more required criteria;
verifying the class as a function of the specific instances associated with the class; and
displaying one or more objects of the class using a graphical user interface (GUI), wherein the GUI enables a user to adjust the class by adding instances, deleting instances, and adjusting instances, wherein the adjustment of the class further comprises an authorization process, wherein the authorization process comprises:
receiving, at the at least a processor, an adjustment signal;
generating a response signal as a function of the comparison of the adjustment signal, the class, and an optimization metric; and
transmitting the response signal to the GUI;
receiving a second object, wherein:
the second object comprises instances of classes comprising one or more values and behaviors; and
the second object is generated by a machine-learning model using natural language processing to identify certain strings within a plurality of second object instances of classes; and
determining an expression of the first object in relation to the second object, wherein determining the expression of the first object in relation to the second object comprises:
inputting the first object and the second object into an expression model trained on historic patient data associated with historic payor data, wherein a large language model is implemented to parse unstructured data of the historic patient data, and performing de-identification of personally identifiable information prior to training the expression model and re-identification after training the expression model in accordance with compliance protocols;
generating, at the expression model, the expression;
outputting the expression; and
returning a value associated with the expression.
12 . The method of claim 11 , wherein the second object further comprises one or more values and behaviors associated with one or more constraints generated from textual data.
13 . The method of claim 12 , wherein the one or more values and behaviors comprise historic data.
14 . The method of claim 11 , wherein the returned value comprises a set of values, wherein the set of values comprises evolving values.
15 . The method of claim 11 , wherein the method further comprises displaying, at a display device, the returned value associated with a relationship between the first object and the second object.
16 . The method of claim 15 , wherein the wherein the GUI comprises one or more event handlers.
17 . The method of claim 11 , wherein the method further comprises transmitting the returned value to a database.
18 . The method of claim 11 , wherein the first object and the second object are updated iteratively with newly occurring instances.
19 . The method of claim 18 , wherein the newly occurring instances are used as new training data to retrain the expression model.
20 . The method of claim 11 , wherein the expression model is trained using exemplary first and second objects correlated to exemplary expressions.