Sholhui Park

Emailsolheeparkewha.ackr

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Comparative evaluation of six large language models in transfusion medicine: Addressing language and domain-specific challenges
Lee, J. K., Park, S., Hwang, S. H., Lee, J., Cho, D. & Choi, S., Apr 2026, In: Vox Sanguinis. 121, 4, p. 496-504 9 p.
Research output: Contribution to journal › Article › peer-review
2 Scopus citations
Evaluation of Six Large Language Models for Clinical Decision Support: Application in Transfusion Decisionmaking for RhD Blood-type Patients
Lee, J. K., Choi, S., Park, S., Hwang, S. H. & Cho, D., 2025, In: Annals of Laboratory Medicine. 45, 5, p. 520-529 10 p.
Research output: Contribution to journal › Article › peer-review

Open Access
3 Scopus citations
What kind of information is requested by patients and families with genetic disorders? The analysis of an online patient community in South Korea
Lee, S. A., Park, S., So, M. K., Chung, H. S., Kim, H. S., Kim, A. & Huh, J., Dec 2025, In: Journal of Community Genetics. 16, 6, p. 787-797 11 p.
Research output: Contribution to journal › Article › peer-review
Deep learning model for differentiating acute myeloid and lymphoblastic leukemia in peripheral blood cell images via myeloblast and lymphoblast classification
Park, S., Park, Y. H., Huh, J., Baik, S. M. & Park, D. J., 1 Jan 2024, In: Digital Health. 10
Research output: Contribution to journal › Article › peer-review

Open Access
22 Scopus citations
Development of blood demand prediction model using artificial intelligence based on national public big data
Kwon, H. J., Park, S., Park, Y. H., Baik, S. M. & Park, D. J., 1 Jan 2024, In: Digital Health. 10
Research output: Contribution to journal › Article › peer-review

Open Access
16 Scopus citations

Sholhui Park

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Collaborations and top research areas from the last five years

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Comparative evaluation of six large language models in transfusion medicine: Addressing language and domain-specific challenges

Evaluation of Six Large Language Models for Clinical Decision Support: Application in Transfusion Decisionmaking for RhD Blood-type Patients

What kind of information is requested by patients and families with genetic disorders? The analysis of an online patient community in South Korea

Deep learning model for differentiating acute myeloid and lymphoblastic leukemia in peripheral blood cell images via myeloblast and lymphoblast classification

Development of blood demand prediction model using artificial intelligence based on national public big data

Sholhui Park

Fingerprint

Collaborations and top research areas from the last five years

Research output

Comparative evaluation of six large language models in transfusion medicine: Addressing language and domain-specific challenges

Evaluation of Six Large Language Models for Clinical Decision Support: Application in Transfusion Decisionmaking for RhD Blood-type Patients

What kind of information is requested by patients and families with genetic disorders? The analysis of an online patient community in South Korea

Deep learning model for differentiating acute myeloid and lymphoblastic leukemia in peripheral blood cell images via myeloblast and lymphoblast classification

Development of blood demand prediction model using artificial intelligence based on national public big data