17. At least one non-transitory computer-readable storage medium encoded with a plurality of computer-executable instructions that, when executed by at least one processor, cause the at least one processor to perform a method comprising: receiving an original free-form text narrative regarding a patient encounter provided by a clinician; re-formatting the original free-form text narrative at least in part by adding, removing, and/or correcting sentence boundaries and/or section boundaries with respect to the original free-form text narrative to produce a formatted text including the added and/or corrected sentence boundaries and/or section boundaries, the re-formatting comprising applying at least one statistical model to the original free-form text narrative to generate, for a word or a sequence of words in the original free-form text narrative, a probability that the word or the sequence of words would be followed by a sentence boundary and/or a section boundary, wherein the at least one statistical model is trained at least in part with other free-form text narratives having correct sentence boundaries and/or section boundaries, and in response to determining that the probability satisfies one or more criteria, adding, removing, and/or correcting a sentence boundary and/or a section boundary following the word or the sequence of words, with respect to the original free-form text narrative; extracting one or more clinical facts from the formatted text, wherein a first fact of the one or more clinical facts is extracted from a first portion of the formatted text, wherein the first portion of the formatted text is a formatted version of a first portion of the original free-form text narrative, the extracting comprising analyzing the formatted text to identify a set of one or more features of at least the first portion of the formatted text, correlating the set of features to one or more abstract semantic concepts, and generating computer-readable data that expresses the one or more abstract semantic concepts as the one or more clinical facts extracted from the formatted text; and providing to a user an indicator that distinguishes the first portion of the original free-form text narrative that resulted in extraction of the first fact, from other portions of the original free-form text narrative that did not result in the extraction of the first fact.
17. At least one non-transitory computer-readable storage medium encoded with a plurality of computer-executable instructions that, when executed by at least one processor, cause the at least one processor to perform a method comprising: receiving an original free-form text narrative regarding a patient encounter provided by a clinician; re-formatting the original free-form text narrative at least in part by adding, removing, and/or correcting sentence boundaries and/or section boundaries with respect to the original free-form text narrative to produce a formatted text including the added and/or corrected sentence boundaries and/or section boundaries, the re-formatting comprising applying at least one statistical model to the original free-form text narrative to generate, for a word or a sequence of words in the original free-form text narrative, a probability that the word or the sequence of words would be followed by a sentence boundary and/or a section boundary, wherein the at least one statistical model is trained at least in part with other free-form text narratives having correct sentence boundaries and/or section boundaries, and in response to determining that the probability satisfies one or more criteria, adding, removing, and/or correcting a sentence boundary and/or a section boundary following the word or the sequence of words, with respect to the original free-form text narrative; extracting one or more clinical facts from the formatted text, wherein a first fact of the one or more clinical facts is extracted from a first portion of the formatted text, wherein the first portion of the formatted text is a formatted version of a first portion of the original free-form text narrative, the extracting comprising analyzing the formatted text to identify a set of one or more features of at least the first portion of the formatted text, correlating the set of features to one or more abstract semantic concepts, and generating computer-readable data that expresses the one or more abstract semantic concepts as the one or more clinical facts extracted from the formatted text; and providing to a user an indicator that distinguishes the first portion of the original free-form text narrative that resulted in extraction of the first fact, from other portions of the original free-form text narrative that did not result in the extraction of the first fact. 24. The at least one non-transitory computer-readable storage medium of claim 17 , wherein neither the original free-form text narrative nor the formatted text is edited by a human other than the clinician before the one or more clinical facts are extracted.