Sangzin Ahn

Assistant Professor

Inje University College of Medicine

South Korea

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About

Dr. Sangzin Ahn is an Assistant Professor at Inje University College of Medicine in South Korea. His research focuses on the application of large language models in medicine, particularly in transfusion medicine and medical education. He has also investigated barriers to health care access, including tuberculosis treatment and biobank utilization. Dr. Ahn's work emphasizes the integration of data science and medical research through innovative methodologies.

Articles (16)

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2025

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2025

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2025

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2024

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2024

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2023

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2023

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2023

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2022

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2022

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2021

Collaborators (2)

Su-Jun Lee

Professor

Inje University College of Medicine

SOUTH KOREA

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Dong Hyun Kim

Professor

Inje University College of Medicine

SOUTH KOREA

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Sangzin Ahn

Research Interests

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About

Articles (16)

Large Language Model Advances in Transfusion Medicine: From Answering Questions to Supporting Clinical Decisions

Barriers and opportunities in biobank utilization: insights from a 3-year repeated cross-sectional survey of the Female Breast and Genital Disease with Microbiome Biobank Network (FDMNet) in South Korea

Public Perceptions and Barriers to Tuberculosis Treatment in Korea: A Large Language Model-Based Analysis of Naver Knowledge-iN Data from 2002 to 2024

A guide to evade hallucinations and maintain reliability when using large language models for medical research: a narrative review

Drug-Drug Interactions between COVID-19 and Tuberculosis Medications: A Comprehensive Review of CYP450 and Transporter-Mediated Effects

Data science through natural language with ChatGPT’s Code Interpreter

Large language model usage guidelines in Korean medical journals: a survey using human-artificial intelligence collaboration

A use case of ChatGPT in a flipped medical terminology course

CYP2C19 Contributes to THP-1-Cell-Derived M2 Macrophage Polarization by Producing 11,12- and 14,15-Epoxyeicosatrienoic Acid, Agonists of the PPARγ Receptor

The impending impacts of large language models on medical education

Tumor Microenvironment and Genes Affecting the Prognosis of Temozolomide-Treated Glioblastoma

Impact of Criterion Versus Norm-Referenced Assessment on the Quality of Life in Korean Medical Students

Transforming clinical trials: the emerging roles of large language models

Center for Personalized Precision Medicine for Tuberculosis: Smart Research and Development Workstation

Building and analyzing machine learning-based warfarin dose prediction models using scikit-learn

Comparison of multivariate linear regression and a machine learning algorithm developed for prediction of precision warfarin dosing in a Korean population

Collaborators (2)

Su-Jun Lee

Dong Hyun Kim

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