Evidence map›Paper›PMID 32734163›Full record

ArticleJAMIA open2020

Artificial intelligence-based conversational agent to support medication prescribing.

Anita M Preininger, Brett South, Jeff Heiland, Adam Buchold, Mya Baca, Suwei Wang, Rex Nipper, Nawshin Kutub, Bryan Bohanan, Gretchen Purcell Jackson

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in JAMIA open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Leveraging conversational technology to answer common COVID-19 questions.Journal of the American Medical Informatics Association : JAMIA · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Anita M PreiningerIBM Watson Health, Cambridge, MA, USA.ORCID 0000-0001-8011-9391
Brett SouthIBM Watson Health, Cambridge, MA, USA.
Jeff HeilandIBM Watson Health, Cambridge, MA, USA.
Adam BucholdIBM Watson Health, Cambridge, MA, USA.
Mya BacaIBM Watson Health, Cambridge, MA, USA.
Suwei WangIBM Watson Health, Cambridge, MA, USA.
Rex NipperIBM Watson Health, Cambridge, MA, USA.
Nawshin KutubIBM Watson Health, Cambridge, MA, USA.
Bryan BohananIBM Watson Health, Cambridge, MA, USA.
Gretchen Purcell JacksonIBM Watson Health, Cambridge, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis article describes the system architecture, training, initial use, and performance of Watson Assistant (WA), an artificial intelligence-based conversational agent, accessible within Micromedex MATERIALS AND

methodsThe number and frequency of

resultsIn over 126 000 conversations with WA, intents most frequently triggered involved dosing ( DISCUSSION: A conversational agent successfully linked most queries to intents in Micromedex. Ongoing system training seeks to widen the scope of WA and improve matching capabilities.

conclusionWA enabled Micromedex users to obtain answers to many medication-related questions using natural language, with the conversational agent facilitating mapping to a broader distribution of topics than standard keyword searches.

Indexed as

artificial intelligenceconversational agentsmachine learningnatural language processingpharmacological information systems

Identifiers

PMID32734163
PMCPMC7382615

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.