MedReadr: Development and Evaluation of an In-Browser, Rule-Based Natural Language Processing Algorithm to Estimate the Reliability of Consumer Health Articles. Article Swipe
Joshua Winograd
,
Autumn Kim
,
Nikit Venishetty
,
Alia Codelia‐Anjum
,
Dean Elterman
,
Naeem Bhojani
,
Kevin C. Zorn
,
Adithya Balasubramanian
,
Andrew J. Vickers
,
Bilal Chughtai
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1159/000548163
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1159/000548163
MedReadr demonstrates that structural reliability scoring of online health articles can be automated using a transparent, rule-based NLP approach. Applied to English-language articles from mainstream search results on common medical conditions, the tool showed strong agreement with validated manual scoring systems. However, it has only been validated on a narrow scope of content and is not designed to analyze search results for specific questions or detect misinformation. Future research should assess its performance across a broader range of web content and evaluate whether its integration improves patient comprehension, digital health literacy, and clinician-patient communication.
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- Type
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- https://www.ncbi.nlm.nih.gov/pmc/articles/12503773
- OA Status
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- References
- 12
- OpenAlex ID
- https://openalex.org/W4415027629
All OpenAlex metadata
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https://openalex.org/W4415027629Canonical identifier for this work in OpenAlex
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https://doi.org/10.1159/000548163Digital Object Identifier
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MedReadr: Development and Evaluation of an In-Browser, Rule-Based Natural Language Processing Algorithm to Estimate the Reliability of Consumer Health Articles.Work title
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articleOpenAlex work type
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enPrimary language
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2025-10-09Full publication date if available
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Joshua Winograd, Autumn Kim, Nikit Venishetty, Alia Codelia‐Anjum, Dean Elterman, Naeem Bhojani, Kevin C. Zorn, Adithya Balasubramanian, Andrew J. Vickers, Bilal ChughtaiList of authors in order
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https://www.ncbi.nlm.nih.gov/pmc/articles/12503773Publisher landing page
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greenOpen access status per OpenAlex
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https://www.ncbi.nlm.nih.gov/pmc/articles/12503773Direct OA link when available
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0Total citation count in OpenAlex
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12Number of works referenced by this work
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| abstract_inverted_index.is | 54 |
| abstract_inverted_index.it | 42 |
| abstract_inverted_index.of | 6, 51, 77 |
| abstract_inverted_index.on | 27, 47 |
| abstract_inverted_index.or | 64 |
| abstract_inverted_index.to | 20, 57 |
| abstract_inverted_index.NLP | 17 |
| abstract_inverted_index.and | 53, 80, 91 |
| abstract_inverted_index.can | 10 |
| abstract_inverted_index.for | 61 |
| abstract_inverted_index.has | 43 |
| abstract_inverted_index.its | 71, 83 |
| abstract_inverted_index.not | 55 |
| abstract_inverted_index.the | 31 |
| abstract_inverted_index.web | 78 |
| abstract_inverted_index.been | 45 |
| abstract_inverted_index.from | 23 |
| abstract_inverted_index.only | 44 |
| abstract_inverted_index.that | 2 |
| abstract_inverted_index.tool | 32 |
| abstract_inverted_index.with | 36 |
| abstract_inverted_index.range | 76 |
| abstract_inverted_index.scope | 50 |
| abstract_inverted_index.using | 13 |
| abstract_inverted_index.Future | 67 |
| abstract_inverted_index.across | 73 |
| abstract_inverted_index.assess | 70 |
| abstract_inverted_index.common | 28 |
| abstract_inverted_index.detect | 65 |
| abstract_inverted_index.health | 8, 89 |
| abstract_inverted_index.manual | 38 |
| abstract_inverted_index.narrow | 49 |
| abstract_inverted_index.online | 7 |
| abstract_inverted_index.search | 25, 59 |
| abstract_inverted_index.should | 69 |
| abstract_inverted_index.showed | 33 |
| abstract_inverted_index.strong | 34 |
| abstract_inverted_index.Applied | 19 |
| abstract_inverted_index.analyze | 58 |
| abstract_inverted_index.broader | 75 |
| abstract_inverted_index.content | 52, 79 |
| abstract_inverted_index.digital | 88 |
| abstract_inverted_index.medical | 29 |
| abstract_inverted_index.patient | 86 |
| abstract_inverted_index.results | 26, 60 |
| abstract_inverted_index.scoring | 5, 39 |
| abstract_inverted_index.whether | 82 |
| abstract_inverted_index.However, | 41 |
| abstract_inverted_index.MedReadr | 0 |
| abstract_inverted_index.articles | 9, 22 |
| abstract_inverted_index.designed | 56 |
| abstract_inverted_index.evaluate | 81 |
| abstract_inverted_index.improves | 85 |
| abstract_inverted_index.research | 68 |
| abstract_inverted_index.specific | 62 |
| abstract_inverted_index.systems. | 40 |
| abstract_inverted_index.agreement | 35 |
| abstract_inverted_index.approach. | 18 |
| abstract_inverted_index.automated | 12 |
| abstract_inverted_index.literacy, | 90 |
| abstract_inverted_index.questions | 63 |
| abstract_inverted_index.validated | 37, 46 |
| abstract_inverted_index.mainstream | 24 |
| abstract_inverted_index.rule-based | 16 |
| abstract_inverted_index.structural | 3 |
| abstract_inverted_index.conditions, | 30 |
| abstract_inverted_index.integration | 84 |
| abstract_inverted_index.performance | 72 |
| abstract_inverted_index.reliability | 4 |
| abstract_inverted_index.demonstrates | 1 |
| abstract_inverted_index.transparent, | 15 |
| abstract_inverted_index.communication. | 93 |
| abstract_inverted_index.comprehension, | 87 |
| abstract_inverted_index.misinformation. | 66 |
| abstract_inverted_index.English-language | 21 |
| abstract_inverted_index.clinician-patient | 92 |
| cited_by_percentile_year | |
| countries_distinct_count | 2 |
| institutions_distinct_count | 10 |
| citation_normalized_percentile.value | 0.61859364 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |