1. A method of analyzing a text documenting a patient encounter, the method comprising: extracting from a first portion of the text, using a fact extraction component implemented via at least one processor, a first set of one or more medical facts representing one or more abstract semantic concepts; receiving information identifying a change made by a user to the first set of medical facts extracted from the first portion of the text, wherein the information identifying the change identifies at least one user-specified abstract semantic concept; updating the fact extraction component based on the at least one user-specified abstract semantic concept and the first portion of the text, wherein the updating comprises: identifying features included in the first portion of the text, the features including one or more tokens and/or one or more N-grams appearing in the first portion of the text; identifying, from among the features identified in the first portion of the text, a first set of features to associate with the at least one user-specified abstract semantic concept, the first set of features including one or more features, the one or more features of the first set including one or more tokens and/or one or more N-grams; and updating the fact extraction component to associate the first set of features with the at least one user-specified abstract semantic concept; and extracting, using the fact extraction component following the updating and using the at least one processor, a second set of one or more medical facts from a second portion of the text, wherein extracting the second set comprises, in response to identifying in the second portion of the text a second set of features corresponding to the first set of features, extracting from the second portion of the text one or more facts corresponding to the at least one user-specified abstract semantic concept, the second set of features including one or more features.
1. A method of analyzing a text documenting a patient encounter, the method comprising: extracting from a first portion of the text, using a fact extraction component implemented via at least one processor, a first set of one or more medical facts representing one or more abstract semantic concepts; receiving information identifying a change made by a user to the first set of medical facts extracted from the first portion of the text, wherein the information identifying the change identifies at least one user-specified abstract semantic concept; updating the fact extraction component based on the at least one user-specified abstract semantic concept and the first portion of the text, wherein the updating comprises: identifying features included in the first portion of the text, the features including one or more tokens and/or one or more N-grams appearing in the first portion of the text; identifying, from among the features identified in the first portion of the text, a first set of features to associate with the at least one user-specified abstract semantic concept, the first set of features including one or more features, the one or more features of the first set including one or more tokens and/or one or more N-grams; and updating the fact extraction component to associate the first set of features with the at least one user-specified abstract semantic concept; and extracting, using the fact extraction component following the updating and using the at least one processor, a second set of one or more medical facts from a second portion of the text, wherein extracting the second set comprises, in response to identifying in the second portion of the text a second set of features corresponding to the first set of features, extracting from the second portion of the text one or more facts corresponding to the at least one user-specified abstract semantic concept, the second set of features including one or more features. 9. The method of claim 1 , wherein correlating the set of features of the first portion of the text to the one or more abstract semantic concepts comprises applying one or more rules and/or one or more statistical models to the set of features.