SUMMARIZATION PROCESSOR FOR UNSTRUCTURED HEALTH CARE DOCUMENTATION RECEIVED FROM OVER A COMMUNICATIONS NETWORK
Document summarization includes receiving an origin document. Document summarization additionally includes a segmentation of the text of the origin document into different text sections and the submission of the different text sections to a large language model (LLM) through a generative AI engine with a pre-cursor directive to prepare for each of the different text sections, a summarization so as to produce a set of summarizations. Document summarization yet further includes a follow-on submission of the summarizations to the LLM of the generative AI engine with the pre-cursor directive to prepare a summarization of the summarizations. Finally, document summarization includes an insertion of the summarization of the summarizations into a summarization document along with each individual summarization of the different text sections and the persistence of the summarization document in the memory.
1 . A document summarization method comprising:
receiving an origin document from over a communications network into memory of a host computing device;
segmenting text of the origin document into different text sections;
submitting the different text sections over the communications network to a large language model (LLM) through a generative artificial intelligence (AI) engine with a pre-cursor directive to prepare for each of the different text sections, a summarization so as to produce a set of summarizations, and further submitting the summarizations to the LLM of the generative AI engine with the pre-cursor directive to prepare a summarization of the summarizations;
inserting the summarization of the summarizations into a summarization document along with each individual summarization of the different text sections; and,
persisting the summarization document in the memory.
2 . The method of claim 1 , wherein the electronic document is a raster image of a document, the method further comprising optical character recognizing the text from the origin document.
3 . The method of claim 1 , further comprising transforming the text of the origin document into a structured document and submitting the structured document to the LLM of the generative AI engine with the pre-cursor directive.
4 . The method of claim 3 , wherein the structured document comprises a set of fields and a corresponding value for each of the fields.
5 . The method of claim 1 , wherein the pre-cursor directive comprises a word count limit.
6 . The method of claim 1 , wherein the pre-cursor directive comprises a spoken language preference for the summarization of the text.
7 . The method of claim 1 , wherein different terms in the summarization document are replaced with reference codes drawn from an index for a contextual domain of the origin document.
8 . A data processing system adapted for document summarization, the system comprising:
a host computing platform comprising one or more computers, each with memory and one or more processing units including one or more processing cores;
network communications circuitry and supporting software logic adapted to manage data communications over a computer communications network;
an optical character recognition engine; and,
a summarization 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 an image of an origin document through the network circuitry from over the communications network into the memory of the host computing platform;
optical character recognizing text of the origin document in the optical character recognition engine;
segmenting the recognized text into different text sections;
submitting the different text sections through the network circuitry over the communications network to a large language model (LLM) through a generative artificial intelligence (AI) engine with a pre-cursor directive to prepare for each of the different text sections, a summarization so as to produce a set of summarizations, and further submitting the summarizations to the LLM of the generative AI engine with the pre-cursor directive to prepare a summarization of the summarizations;
inserting the summarization of the summarizations into a summarization document along with each individual summarization of the different text sections; and,
persisting the summarization document in the memory.
9 . The system of claim 8 , wherein the program instructions are further enabled to perform transforming the text of the origin document into a structured document and submitting the structured document to the LLM of the generative AI engine with the pre-cursor directive.
10 . The system of claim 9 , wherein the structured document comprises a set of fields and a corresponding value for each of the fields.
11 . The system of claim 8 , wherein the pre-cursor directive comprises a word count limit.
12 . The system of claim 8 , wherein the pre-cursor directive comprises a spoken language preference for the summarization of the text.
13 . The system of claim 8 , wherein different terms in the summarization document are replaced with reference codes drawn from an index for a contextual domain of the origin document.
14 . 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 document summarization comprising:
receiving an origin document from over a communications network into memory of a host computing device;
segmenting text of the origin document into different text sections;
submitting the different text sections over the communications network to a large language model (LLM) through a generative artificial intelligence (AI) engine with a pre-cursor directive to prepare for each of the different text sections, a summarization so as to produce a set of summarizations, and further submitting the summarizations to the LLM of the generative AI engine with the pre-cursor directive to prepare a summarization of the summarizations;
inserting the summarization of the summarizations into a summarization document along with each individual summarization of the different text sections; and,
persisting the summarization document in the memory.
15 . The device of claim 14 , wherein the electronic document is a raster image of a document, the method further comprising optical character recognizing the text from the origin document.
16 . The device of claim 14 , wherein the document summarization further includes transforming the text of the origin document into a structured document and submitting the structured document to the LLM of the generative AI engine with the pre-cursor directive.
17 . The device of claim 16 , wherein the structured document comprises a set of fields and a corresponding value for each of the fields.
16 . The device of claim 14 , wherein the pre-cursor directive comprises a word count limit.
17 . The device of claim 14 , wherein the pre-cursor directive comprises a spoken language preference for the summarization of the text.
20 . The device of claim 14 , wherein different terms in the summarization document are replaced with reference codes drawn from an index for a contextual domain of the origin document.