US 11,869,509 B1
Document generation from conversational sources
Emin Agassi, Blue Bell, PA (US); Tanuj Gupta, Leawood, KS (US); and Leo V. Perez, Platte City, MO (US)
Assigned to Cerner Innovation, Inc., Kansas City, MO (US)
Filed by CERNER INNOVATION, INC., Kansas City, KS (US)
Filed on Dec. 19, 2019, as Appl. No. 16/720,632.
Claims priority of provisional application 62/783,688, filed on Dec. 21, 2018.
Claims priority of provisional application 62/783,695, filed on Dec. 21, 2018.
This patent is subject to a terminal disclaimer.
Int. Cl. G10L 17/00 (2013.01); G16H 10/60 (2018.01)
CPC G10L 17/00 (2013.01) [G16H 10/60 (2018.01)] 14 Claims
OG exemplary drawing
 
1. Non-transitory computer-readable-readable media having computer-executable instructions embodied thereon that when executed, provide a method for enhanced natural language processing, the method comprising:
receiving a voice conversation associated with an individual;
parsing and extracting at least one clinical condition within the voice conversation using one or more natural language processing techniques;
identifying one or more clinical concepts related to the clinical condition using one or more clinical ontologies for the at least one clinical condition, each clinical ontology providing contextual relationships between the clinical condition and the one or more clinical concepts;
verifying each concept of the one or more clinical concepts within the voice conversation by searching structured data in one or more validation sources;
validating at least one concept of the one or more clinical concepts by determining that structured data in at least one of the one or more validation sources is determined to correspond to the at least one concept of the one or more clinical concepts within the voice conversation;
identifying an error within at least one concept of the one or more clinical concepts of the voice conversation based on the one or more validation sources; and
generating one or more outputs that include the at least one concept of the one or more concepts that is determined to be validated based on the one or more validation sources and an indication of the error, wherein the indication of the error includes each of the error, at least a portion of the voice conversation related to the error, and at least a portion of the structured data from the one or more validation sources conflicting with the voice conversation.