PRIORITY CLAIM

This U.S. patent application claims priority under 35 U.S.C. § 119 to: India Application No. 201921041908, filed on 16 Oct. 2019. The entire contents of the aforementioned application are incorporated herein by reference.

TECHNICAL FIELD

This disclosure relates generally relates to data management system, and, more particularly, to system and method for machine assisted documentation in medical writing.

BACKGROUND

During clinical trials process, many documents are prepared i.e. starting from protocol to clinical study report etc. Medical writing requires special skill to produce well-structured documents that present information clearly and concisely, but manual process of creating, updating and maintaining these documents is expensive and time consuming. One of biggest challenge is lack of standardization for the medical writing. In present scenario, unavailability of any standard corpus for training of algorithms in especially in pharmaceutical domain, that is corpus need to be prepared from scratch. The pharmaceutical industry is highly compliance driven regulated industry, output of system must be compliant to different regulations.

SUMMARY

Embodiments of the present disclosure present technological improvements as solutions to one or more of the above-mentioned technical problems recognized by the inventors in conventional systems. For example, in one aspect, a processor implemented method a machine assisted documentation in a medical writing is provided. The processor implemented method includes at least one of: receiving, via one or more hardware processors, a plurality of input documents as an input for different type of documents to be created; processing, via the one or more hardware processors, the inputted plurality of documents by extracting into an at least one section to generate a list of sections; classifying, via the one or more hardware processors, at least one category corresponding to the at least one section to generate a summary set; generating, via the one or more hardware processors, at least one of (i) a local context, (ii) a global context, and combination thereof based on the summary set; parsing, via the one or more hardware processors, at least one sentence based on the generated local context, or global context to generate at least one sequence of the plurality of sentences; processing, via the one or more hardware processors, the at least one sequence of the plurality of sentence to generate a queue of the at least one sequence; and validating, via the one or more hardware processors, the queue of the at least one sequence to obtain a combined summary set. In an embodiment, the at least one category corresponds to a Summarizable category. In an embodiment, the summary set comprises a plurality of sentences.

In an embodiment, the plurality of logical categories may correspond to at least one of (i) a Summarizable sections, (ii) brief summaries, and (iii) text sections excluded. In an embodiment, the Summarizable Sections category may include at least one section of (i) introduction, (ii) problem statement, (iii) research methodology, and (iv) experimentation with associated results. In an embodiment, the brief summaries category may include at least one section of (i) abstract, and (ii) conclusion. In an embodiment, the text sections excluded category may include at least one section of (i) historical background, (ii) references, and (iii) appendix. In an embodiment, the local context may include at least one of (i) overall context of the input documents, (ii) an extracted context of a plurality of referenced documents or combination thereof.

In another aspect, there is provided a processor implemented system for a machine assisted documentation in a medical writing is provided. The system comprises a memory storing instructions; one or more communication interfaces; and one or more hardware processors coupled to the memory via the one or more communication interfaces, wherein the one or more hardware processors are configured by the instructions to: receive, a plurality of input documents as an input for different type of documents to be created; process, the inputted plurality of documents by extracting into an at least one section to generate a list of sections; classify, at least one category corresponding to the at least one section to generate a summary set; generate, at least one of (i) a local context, (ii) a global context, and combination thereof based on the summary set; parse, at least one sentence based on the generated local context, or global context to generate at least one sequence of the plurality of sentences; process, the at least one sequence of the plurality of sentence to generate a queue of the at least one sequence; and validate, the queue of the at least one sequence to obtain a combined summary set. In an embodiment, the at least one category corresponds to a Summarizable category. In an embodiment, the summary set comprises a plurality of sentences.

In an embodiment, the plurality of logical categories may correspond to at least one of (i) a Summarizable sections, (ii) brief summaries, and (iii) text sections excluded. In an embodiment, the Summarizable Sections category may include at least one section of (i) introduction, (ii) problem statement, (iii) research methodology, and (iv) experimentation with associated results. In an embodiment, the brief summaries category may include at least one section of (i) abstract, and (ii) conclusion. In an embodiment, the text sections excluded category may include at least one section of (i) historical background, (ii) references, and (iii) appendix. In an embodiment, the local context may include at least one of (i) overall context of the input documents, (ii) an extracted context of a plurality of referenced documents or combination thereof.

In yet another aspect, there are provided one or more non-transitory machine readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors causes at least one of: receiving, via one or more hardware processors, a plurality of input documents as an input for different type of documents to be created; processing, via the one or more hardware processors, the inputted plurality of documents by extracting into an at least one section to generate a list of sections; classifying, via the one or more hardware processors, at least one category corresponding to the at least one section to generate a summary set; generating, via the one or more hardware processors, at least one of (i) a local context, (ii) a global context, and combination thereof based on the summary set; parsing, via the one or more hardware processors, at least one sentence based on the generated local context, or global context to generate at least one sequence of the plurality of sentences; processing, via the one or more hardware processors, the at least one sequence of the plurality of sentence to generate a queue of the at least one sequence; and validating, via the one or more hardware processors, the queue of the at least one sequence to obtain a combined summary set. In an embodiment, the at least one category corresponds to a Summarizable category. In an embodiment, the summary set comprises a plurality of sentences.

In an embodiment, the plurality of logical categories may correspond to at least one of (i) a Summarizable sections, (ii) brief summaries, and (iii) text sections excluded. In an embodiment, the Summarizable Sections category may include at least one section of (i) introduction, (ii) problem statement, (iii) research methodology, and (iv) experimentation with associated results. In an embodiment, the brief summaries category may include at least one section of (i) abstract, and (ii) conclusion. In an embodiment, the text sections excluded category may include at least one section of (i) historical background, (ii) references, and (iii) appendix. In an embodiment, the local context may include at least one of (i) overall context of the input documents, (ii) an extracted context of a plurality of referenced documents or combination thereof.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.

