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UID:pretalx-chla-absc-2026-NSNYVL@pretalx.com
DTSTART;TZID=EST:20260604T143000
DTEND;TZID=EST:20260604T145000
DESCRIPTION:<b>Introduction</b>\nSince April 2022\, indexing of MEDLINE rec
 ords is performed predominantly by algorithm\, with occasional human inter
 vention. Recent research has raised concerns about indexing algorithms’ 
 capacity to accurately identify meaningful elements of publications. This 
 identification is a necessary precondition to communicating them to search
 ers through indexing. Concerns have included the risk of the algorithm ove
 rlooking one or more relevant concepts\, not making use of appropriately p
 recise controlled vocabulary\, or assigning incorrect terms due to rhetori
 cal or technical language. The indexing algorithm from 2022-2024 (MTIA) wa
 s a rule-based system with exceptions added over time\; a machine learning
  model (MTIX) was implemented in 2024. NLM Technical Bulletins have noted 
 general improvements in MTIX compared to MTIA. Recent research has explore
 d particularities of evocative language and found improvements in discerni
 ng human from nonhuman-animal subjects.   \n<b>METHODS</b>\nThis work will
  replicate and improve on a previous project that assessed overall MTIA in
 dexing performance. Our study will assess MTIX performance by reviewing a 
 large\, recent and random sample of MTIX-indexed records to determine whet
 her their main concepts are adequately represented. \nUsing a web-form dis
 playing the journal\, title and abstract of a record\, our screeners will 
 identify key concepts that\, per their searching experience\, would be use
 d to retrieve it and similar records. After establishing agreement between
  screeners\, we will compare the consensus-concepts to the indexing applie
 d by MTIX. We will compare these findings to previous research\, noting em
 ergent trends or issues.  \n\n<b>RESULTS & CONCLUSION</b>  \nWe intend to 
 make our web-form freely available online. Other results are forthcoming.
DTSTAMP:20260506T115351Z
LOCATION:Borduas-Krieghoff2
SUMMARY:Assessing the performance of the National Library of Medicine’s M
 edical Text Indexer - neXt-generation (MTIX) MEDLINE indexing algorithm - 
 Alexandre Amar-Zifkin\, Tara Landry\, Rosie Le Faive
URL:https://pretalx.com/chla-absc-2026/talk/NSNYVL/
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