class_docstr: "Paragraph-level Simplification of Medical Texts" (Devaraj et al.) studies the problem of learning to simplify
  medical texts. One of their contributions is a new corpus that is composed of technical abstracts and their
  lay summaries on various clinical topics.
  
  The author generated train/val/test splits, which are available in the GitHub repository linked in the paper.
  
  The following is an example from the dataset:
  
  {
      "doi": "10.1002/14651858.CD011112.pub2",
      "abstract": "We included six studies (reported as seven papers) involving 326 participants whose ages ranged
      from 39 to 83 years, with a gender bias towards men (73% to 95% across studies), reflecting the characteristics
      of patients with HNC. The risk of bias in the studies was generally high. We did not pool data from studies
      because of significant differences in the interventions and outcomes evaluated. We found a lack of
      standardisation and consistency in the outcomes measured and the endpoints at which they were evaluated.
      We found no evidence that therapeutic exercises were better than TAU, or any other treatment, in improving the
      safety and efficiency of oral swallowing (our primary outcome) or in improving any of the secondary outcomes.
      Using the GRADE system, we classified the overall quality of the evidence for each outcome as very low, due to
      the limited number of trials and their low quality. There were no adverse events reported that were directly
      attributable to the intervention (swallowing exercises). We found no evidence that undertaking therapeutic
      exercises before, during and/or immediately after HNC treatment leads to improvement in oral swallowing. This
      absence of evidence may be due to the small participant numbers in trials, resulting in insufficient power to
      detect any difference. Data from the identified trials could not be combined due to differences in the choice
      of primary outcomes and in the measurement tools used to assess them, and the differing baseline and endpoints
      across studies. Designing and implementing studies with stronger methodological rigour is essential. There needs
      to be agreement about the key primary outcomes, the choice of validated assessment tools to measure them and the
      time points at which those measurements are made.",
      "pls": "We included six studies with 326 participants who undertook therapeutic exercises before, during and/or
      after HNC treatment. We could not combine the results of the studies because of the variation in participants'
      cancers, their treatments, the outcomes measured and the tools used to assess them, as well as the differing
      time points for testing. Researchers have compared: (i) therapeutic exercises versus treatment as usual (TAU);
      (ii) therapeutic exercises versus sham therapy; (iii) therapeutic exercises plus TAU versus TAU. The therapeutic
      exercises varied in their design, timing and intensity. TAU involved managing patients' dysphagia when it
      occurred, including inserting a tube for non-oral feeding. The evidence is up to date to 1 July 2016. We found
      no evidence that therapeutic exercises were better than TAU, or any other treatment, in improving the safety and
      efficiency of oral swallowing (our primary outcome) or in improving any of the secondary outcomes. However,
      there is insufficient evidence to draw any clear conclusion about the effects of undertaking therapeutic
      exercises before during and/or immediately after HNC treatment on preventing or reducing dysphagia. Studies had
      small participant numbers, used complex interventions and varied in the choice of outcomes measured, making it
      difficult to draw reliable conclusions. There were no reported adverse events directly attributable to the
      intervention (swallowing exercises). The current quality of the evidence to support the use of therapeutic
      exercises before, during and/or immediately after HNC treatment to prevent/reduce dysphagia is very low. We need
      better designed, rigorous studies with larger participant numbers and agreed endpoints and outcome measurements
      in order to draw clear(er) conclusions."
  },
  
  where "pls" stands for "plain-language summary".
  
  Paper: http://arxiv.org/abs/2104.05767
  Code: https://github.com/AshOlogn/Paragraph-level-Simplification-of-Medical-Texts
  
  @inproceedings{devaraj-etal-2021-paragraph,
      title = "Paragraph-level Simplification of Medical Texts",
      author = "Devaraj, Ashwin and Marshall, Iain and Wallace, Byron and Li, Junyi Jessy",
      booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for
                   Computational Linguistics",
      month = jun,
      year = "2021",
      publisher = "Association for Computational Linguistics",
      url = "https://www.aclweb.org/anthology/2021.naacl-main.395",
      pages = "4972--4984",
  }
class_docstr_tok: ["``","Paragraph-level","Simplification","of","Medical","Texts","''","(","Devaraj","et","al",".",")","studies","the","problem","of","learning","to","simplify","medical","texts",".","One","of","their","contributions","is","a","new","corpus","that","is","composed","of","technical","abstracts","and","their","lay","summaries","on","various","clinical","topics",".","The","author","generated","train\/val\/test","splits",",","which","are","available","in","the","GitHub","repository","linked","in","the","paper",".","The","following","is","an","example","from","the","dataset",":","{","``","doi","''",":","``","10.1002\/14651858.CD011112.pub2","''",",","``","abstract","''",":","``","We","included","six","studies","(","reported","as","seven","papers",")","involving","326","participants","whose","ages","ranged","from","39","to","83","years",",","with","a","gender","bias","towards","men","(","73","%","to","95","%","across","studies",")",",","reflecting","the","characteristics","of","patients","with","HNC",".","The","risk","of","bias","in","the","studies","was","generally","high",".","We","did","not","pool","data","from","studies","because","of","significant","differences","in","the","interventions","and","outcomes","evaluated",".","We","found","a","lack","of","standardisation","and","consistency","in","the","outcomes","measured","and","the","endpoints","at","which","they","were","evaluated",".","We","found","no","evidence","that","therapeutic","exercises","were","better","than","TAU",",","or","any","other","treatment",",","in","improving","the","safety","and","efficiency","of","oral","swallowing","(","our","primary","outcome",")","or","in","improving","any","of","the","secondary","outcomes",".","Using","the","GRADE","system",",","we","classified","the","overall","quality","of","the","evidence","for","each","outcome","as","very","low",",","due","to","the","limited","number","of","trials","and","their","low","quality",".","There","were","no","adverse","events","reported","that","were","directly","attributable","to","the","intervention","(","swallowing","exercises",")",".","We","found","no","evidence","that","undertaking","therapeutic","exercises","before",",","during","and\/or","immediately","after","HNC","treatment","leads","to","improvement","in","oral","swallowing",".","This","absence","of","evidence","may","be","due","to","the","small","participant","numbers","in","trials",",","resulting","in","insufficient","power","to","detect","any","difference",".","Data","from","the","identified","trials","could","not","be","combined","due","to","differences","in","the","choice","of","primary","outcomes","and","in","the","measurement","tools","used","to","assess","them",",","and","the","differing","baseline","and","endpoints","across","studies",".","Designing","and","implementing","studies","with","stronger","methodological","rigour","is","essential",".","There","needs","to","be","agreement","about","the","key","primary","outcomes",",","the","choice","of","validated","assessment","tools","to","measure","them","and","the","time","points","at","which","those","measurements","are","made",".","``",",","``","pls","''",":","``","We","included","six","studies","with","326","participants","who","undertook","therapeutic","exercises","before",",","during","and\/or","after","HNC","treatment",".","We","could","not","combine","the","results","of","the","studies","because","of","the","variation","in","participants'","cancers",",","their","treatments",",","the","outcomes","measured","and","the","tools","used","to","assess","them",",","as","well","as","the","differing","time","points","for","testing",".","Researchers","have","compared",":","(","i",")","therapeutic","exercises","versus","treatment","as","usual","(","TAU",")",";","(","ii",")","therapeutic","exercises","versus","sham","therapy",";","(","iii",")","therapeutic","exercises","plus","TAU","versus","TAU",".","The","therapeutic","exercises","varied","in","their","design",",","timing","and","intensity",".","TAU","involved","managing","patients","'","dysphagia","when","it","occurred",",","including","inserting","a","tube","for","non-oral","feeding",".","The","evidence","is","up","to","date","to","1","July","2016",".","We","found","no","evidence","that","therapeutic","exercises","were","better","than","TAU",",","or","any","other","treatment",",","in","improving","the","safety","and","efficiency","of","oral","swallowing","(","our","primary","outcome",")","or","in","improving","any","of","the","secondary","outcomes",".","However",",","there","is","insufficient","evidence","to","draw","any","clear","conclusion","about","the","effects","of","undertaking","therapeutic","exercises","before","during","and\/or","immediately","after","HNC","treatment","on","preventing","or","reducing","dysphagia",".","Studies","had","small","participant","numbers",",","used","complex","interventions","and","varied","in","the","choice","of","outcomes","measured",",","making","it","difficult","to","draw","reliable","conclusions",".","There","were","no","reported","adverse","events","directly","attributable","to","the","intervention","(","swallowing","exercises",")",".","The","current","quality","of","the","evidence","to","support","the","use","of","therapeutic","exercises","before",",","during","and\/or","immediately","after","HNC","treatment","to","prevent\/reduce","dysphagia","is","very","low",".","We","need","better","designed",",","rigorous","studies","with","larger","participant","numbers","and","agreed","endpoints","and","outcome","measurements","in","order","to","draw","clear","(","er",")","conclusions",".","''","}",",","where","``","pls","''","stands","for","``","plain-language","summary","''",".","Paper",":","http",":","\/\/arxiv.org\/abs\/2104.05767","Code",":","https",":","\/\/github.com\/AshOlogn\/Paragraph-level-Simplification-of-Medical-Texts","@","inproceedings","{","devaraj-etal-2021-paragraph",",","title","=","``","Paragraph-level","Simplification","of","Medical","Texts","''",",","author","=","``","Devaraj",",","Ashwin","and","Marshall",",","Iain","and","Wallace",",","Byron","and","Li",",","Junyi","Jessy","''",",","booktitle","=","``","Proceedings","of","the","2021","Conference","of","the","North","American","Chapter","of","the","Association","for","Computational","Linguistics","''",",","month","=","jun",",","year","=","``","2021","''",",","publisher","=","``","Association","for","Computational","Linguistics","''",",","url","=","``","https",":","\/\/www.aclweb.org\/anthology\/2021.naacl-main.395","''",",","pages","=","``","4972","--","4984","''",",","}"]
code: def get_instances(self) -> List[Instance]:
      data_path: str = os.path.join(self.output_path, "data")
      ensure_directory_exists(data_path)
  
      instances: List[Instance] = []
      for split in ALL_SPLITS:
          # Original abstracts
          abstract_file_name: str = (
              f"{'val' if split == VALID_SPLIT else split}.source"
          )
          abstract_path: str = os.path.join(
              data_path, abstract_file_name
          )
          ensure_file_downloaded(
              source_url=MedParagraphSimplificationScenario.DOWNLOAD_URL_TEMPLATE.format(
                  file_name=abstract_file_name
              ),
              target_path=abstract_path,
          )
  
          # Plain-language summaries of the abstracts
          pls_file_name: str = (
              f"{'val' if split == VALID_SPLIT else split}.target"
          )
          pls_path: str = os.path.join(data_path, pls_file_name)
          ensure_file_downloaded(
              source_url=MedParagraphSimplificationScenario.DOWNLOAD_URL_TEMPLATE.format(
                  file_name=pls_file_name
              ),
              target_path=pls_path,
          )
  
          with open(abstract_path, "r") as abstract_file:
              with open(pls_path, "r") as pls_file:
                  for abstract_line, summary_line in zip(
                      abstract_file, pls_file
                  ):
                      abstract: str = abstract_line.rstrip()
                      summary: str = summary_line.rstrip()
                      instance: Instance = Instance(
                          input=Input(text=abstract),
                          references=[
                              Reference(
                                  Output(text=summary),
                                  tags=[CORRECT_TAG],
                              )
                          ],
                          split=split,
                      )
                      instances.append(instance)
  
      return instances
  
imports: import os
  from typing import List
  from helm.common.general import ensure_directory_exists, ensure_file_downloaded
  from .scenario import Scenario, Instance, Reference, ALL_SPLITS, CORRECT_TAG, VALID_SPLIT, Input, Output
label_desc: Use image node_id 1 for calling the MedParagraphSimplificationScenario obj's underlying member method code with example usage: obj.get_instances() and returns: instances