Automated indexing and extraction of multiple information fields in digital records

A computer implemented method comprising:

• identifying, based on rules defining target information fields, for each target field of the target information fields, at least one page in a digital data record comprising content related to the target field;
• extracting, for each target field, from the at least one page, at least one portion of text comprising the content;
• feeding, for each target field, a pre-processed version of the at least one portion of text into a machine learning (ML) model, wherein the ML model is trained on data associated with the target field;
• determining, for each target field, via the ML model trained on the target field, at least one candidate text comprising the content;
• extracting, for each target field, the at least one candidate text;
• identifying a page of the digital data record containing special target information;
• inputting an image of the page into a visual machine learning network (visual ML), wherein the visual ML is trained to recognize text associated with the special target information in an image;
• identifying by the visual ML, a section of the image that contains the special target information;
• inputting a page number of the page, the digital data record, and coordinates of the section into an extraction module;
• and
• extracting the special target information by the extraction module from the section.

A system to automatically index multiple informational fields in a digital data record, the system comprising:

• a plurality of trained NLP ML models, wherein each ML model of the plurality of trained NLP ML models is trained on a specific target information field of a plurality of target information fields;
• a database to store indexed information;
• a memory comprising instructions, coupled to a processor, wherein the instructions are executable by a processor to:
• identify, based on rules defining the target information fields, for each target field of the target information fields, at least one page in the digital data record comprising content related to the target field;
• extract, for each target field, from the at least one page, at least one portion of text comprising the content;
• feed, for each target field, a pre-processed version of the at least one portion of text into an ML model of the plurality of trained NLP ML models, wherein the ML model is trained on the target field;
• determine, for each target field, via the ML model trained on the target field, at least one candidate text comprising the content;
• extract, for each target field, via the ML model trained on the target field, the at least one candidate text;
• and
• generate for each target field, via the ML model trained on the target field, an index of the at least one candidate text.

A non-transitory computer-readable storage medium having embodied thereon a program, the program executable by a processor to perform a method for automatically indexing multiple informational fields in a digital data record comprising:

• inputting at least one page identifier of at least one page of a digital data record, into an extraction module, wherein the at least one page identifier comprises at least one of a page number or other page identifier;
• extracting, by the extraction module, for each target field, from the at least one page, wherein the at least one page is based on at least the one page identifier, at least one portion of text comprising content related to a specific target information field;
• feeding, for each target field, a pre-processed version of the at least one portion of text into a machine learning (ML) model, wherein the ML model is trained on the target field;
• determining, for each target field, via the ML model trained on the target field, at least one candidate text comprising the content;
• and
• extracting, for each target field, the at least one candidate text.