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A linguistic lens into vision-language models for open-ended question-answers in medical visual question answering.

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Title: A linguistic lens into vision-language models for open-ended question-answers in medical visual question answering.
Authors: Lameesa A; Information and Communication Technology, Griffith University, Gold Coast, Queensland, Australia., Bin Alam MS; Information and Communication Technology, Griffith University, Gold Coast, Queensland, Australia., Mohi Uddin KM; Department of Computer Science and Engineering, Southeast University, Dhaka, Bangladesh., Muhammad Masum AK; Department of Computer Science and Engineering, Southeast University, Dhaka, Bangladesh.
Source: Digital health [Digit Health] 2026 May 06; Vol. 12, pp. 20552076261450386. Date of Electronic Publication: 2026 May 06 (Print Publication: 2026).
Publication Type: Journal Article
Journal Info: Publisher: SAGE Publications Ltd Country of Publication: United States NLM ID: 101690863 Publication Model: eCollection Cited Medium: Print ISSN: 2055-2076 (Print) Linking ISSN: 20552076 NLM ISO Abbreviation: Digit Health Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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  Data: A linguistic lens into vision-language models for open-ended question-answers in medical visual question answering.
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  Data: <searchLink fieldCode="AU" term="%22Lameesa+A%22">Lameesa A</searchLink>; Information and Communication Technology, Griffith University, Gold Coast, Queensland, Australia.<br /><searchLink fieldCode="AU" term="%22Bin+Alam+MS%22">Bin Alam MS</searchLink>; Information and Communication Technology, Griffith University, Gold Coast, Queensland, Australia.<br /><searchLink fieldCode="AU" term="%22Mohi+Uddin+KM%22">Mohi Uddin KM</searchLink>; Department of Computer Science and Engineering, Southeast University, Dhaka, Bangladesh.<br /><searchLink fieldCode="AU" term="%22Muhammad+Masum+AK%22">Muhammad Masum AK</searchLink>; Department of Computer Science and Engineering, Southeast University, Dhaka, Bangladesh.
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  Data: <searchLink fieldCode="JN" term="%22101690863%22">Digital health</searchLink> [Digit Health] 2026 May 06; Vol. 12, pp. 20552076261450386. <i>Date of Electronic Publication: </i>2026 May 06 (<i>Print Publication: </i>2026).
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22SAGE+Publications+Ltd%22">SAGE Publications Ltd </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101690863 <i>Publication Model: </i>eCollection <i>Cited Medium: </i>Print <i>ISSN: </i>2055-2076 (Print) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2220552076%22">20552076 </searchLink><i>NLM ISO Abbreviation: </i>Digit Health <i>Subsets: </i>PubMed not MEDLINE
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        Value: 10.1177/20552076261450386
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      – Code: eng
        Text: English
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      – TitleFull: A linguistic lens into vision-language models for open-ended question-answers in medical visual question answering.
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            NameFull: Lameesa A
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            NameFull: Bin Alam MS
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            – D: 06
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              Text: 2026 May 06
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              Y: 2026
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