Real-world insights of patient voices with age-related macular degeneration in the Republic of Korea and Taiwan: an AI-based Digital Listening study by Semantic-Natural Language Processing

Digital Listening using Semantic-NLP can provide real-world insights from large amounts of internet data quickly and with low human labour cost. This allows healthcare companies to respond to the unmet needs of patients for effective and safe treatment and improved patient quality of life throughout the product lifecycle.

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Publication Details

Journal
BMC Medical Informatics and Decision Making
Published
2025-03-18
DOI
https://doi.org/10.1186/s12911-025-02929-5
Citations
1
Primary Topic
Retinal Imaging and Analysis
Type
article
Field-Weighted Citation Impact
1.36
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article

Real-world insights of patient voices with age-related macular degeneration in the Republic of Korea and Taiwan: an AI-based Digital Listening study by Semantic-Natural Language Processing

Hyewon Jeon, Yin-ngai Ng, Su‐Yeon Yu, Irina V. Efimenko et al.
1 citations
BMC Medical Informatics and Decision Making
Retinal Imaging and Analysis
1.36
article

Real-world insights of patient voices with age-related macular degeneration in the Republic of Korea and Taiwan: an AI-based Digital Listening study by Semantic-Natural Language Processing

Hyewon Jeon, Yin-ngai Ng, Su‐Yeon Yu, Irina V. Efimenko, Ying Xuan Lim, Huang Yun, Olga Chertkova, Djoubeir Mohamed Makhlouf
article en
1 citations

Abstract

Digital Listening using Semantic-NLP can provide real-world insights from large amounts of internet data quickly and with low human labour cost. This allows healthcare companies to respond to the unmet needs of patients for effective and safe treatment and improved patient quality of life throughout the product lifecycle.

BMC Medical Informatics and Decision MakingVol. 25(1)
Roche (Switzerland) (CH), Kangwon National University (KR), Roche (United Kingdom) (GB), Roche (China) (CN), Roche (South Korea) (KR)
Quality Education
Openalex Percentile: Top 22%
Retinal Imaging and Analysis
1.36
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