Taehoon Ko

1.0k total citations
42 papers, 606 citations indexed

About

Taehoon Ko is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Health Information Management. According to data from OpenAlex, Taehoon Ko has authored 42 papers receiving a total of 606 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 8 papers in Radiology, Nuclear Medicine and Imaging and 7 papers in Health Information Management. Recurrent topics in Taehoon Ko's work include Topic Modeling (3 papers), Retinal Imaging and Analysis (3 papers) and Artificial Intelligence in Healthcare (3 papers). Taehoon Ko is often cited by papers focused on Topic Modeling (3 papers), Retinal Imaging and Analysis (3 papers) and Artificial Intelligence in Healthcare (3 papers). Taehoon Ko collaborates with scholars based in South Korea, United States and Nigeria. Taehoon Ko's co-authors include Sae Won Choi, Kyung Hwan Kim, Sungzoon Cho, Myung Hwan Yun, Ye Seul Bae, Ki Jeong Hong, Ilsun Rhiu, Wonjoon Kim, Du Hyun Ro and Myung Chul Lee and has published in prestigious journals such as The Journal of Clinical Endocrinology & Metabolism, Scientific Reports and Ophthalmology.

In The Last Decade

Taehoon Ko

34 papers receiving 589 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Taehoon Ko South Korea	13	161	123	83	71	67	42	606
Tomohiro Kuroda Japan	16	216 1.3×	113 0.9×	53 0.6×	120 1.7×	67 1.0×	165	1.2k
Yilin Ning Singapore	17	104 0.6×	230 1.9×	33 0.4×	68 1.0×	89 1.3×	58	822
Michelle R. Hribar United States	17	125 0.8×	107 0.9×	83 1.0×	49 0.7×	380 5.7×	70	954
Farkhondeh Asadi Iran	19	299 1.9×	307 2.5×	38 0.5×	48 0.7×	186 2.8×	93	977
Peter Weller United Kingdom	11	86 0.5×	163 1.3×	18 0.2×	94 1.3×	72 1.1×	29	550
Nida Shahid Canada	6	71 0.4×	84 0.7×	21 0.3×	27 0.4×	51 0.8×	18	422
Daniel Fabbri United States	16	95 0.6×	317 2.6×	10 0.1×	57 0.8×	127 1.9×	79	1.0k
Vajira Thambawita Norway	10	183 1.1×	247 2.0×	14 0.2×	31 0.4×	42 0.6×	33	792
Abu Saleh Mohammad Mosa United States	13	43 0.3×	74 0.6×	12 0.1×	83 1.2×	138 2.1×	51	1.2k
Luke Oakden‐Rayner Australia	13	490 3.0×	528 4.3×	28 0.3×	73 1.0×	99 1.5×	18	1.4k

Countries citing papers authored by Taehoon Ko

Since Specialization

Citations

This map shows the geographic impact of Taehoon Ko's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Taehoon Ko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Taehoon Ko more than expected).

Fields of papers citing papers by Taehoon Ko

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Taehoon Ko. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Taehoon Ko. The network helps show where Taehoon Ko may publish in the future.

Co-authorship network of co-authors of Taehoon Ko

This figure shows the co-authorship network connecting the top 25 collaborators of Taehoon Ko. A scholar is included among the top collaborators of Taehoon Ko based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Taehoon Ko. Taehoon Ko is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Lin, Ning, et al.. (2025). Geospatial suitability analysis for data center placement: A case study in Texas, USA. Sustainable Cities and Society. 131. 106687–106687.

Choi, Youngha, et al.. (2025). Development and validation of a machine learning model for predicting pediatric metabolic syndrome using anthropometric and bioelectrical impedance parameters. International Journal of Obesity. 49(6). 1159–1165. 1 indexed citations

Chae, Hyun Wook, et al.. (2025). Development of a Machine Learning-based Model for Methimazole Dosage Adjustment in Youth With Hyperthyroidism. The Journal of Clinical Endocrinology & Metabolism. 111(4). e1136–e1145. 1 indexed citations

Ko, Taehoon, et al.. (2025). Height estimation in children and adolescents using body composition big data: Machine-learning and explainable artificial intelligence approach. Digital Health. 11. 609975591–609975591. 2 indexed citations

Chun, Ji‐Won, et al.. (2024). Comparison of AI with and without hand-crafted features to classify Alzheimer's disease in different languages. Computers in Biology and Medicine. 180. 108950–108950. 2 indexed citations

Song, Kyungchul, Taehoon Ko, Hyun Wook Chae, et al.. (2024). Development and Validation of a Prediction Model Using Sella Magnetic Resonance Imaging–Based Radiomics and Clinical Parameters for the Diagnosis of Growth Hormone Deficiency and Idiopathic Short Stature: Cross-Sectional, Multicenter Study. Journal of Medical Internet Research. 26. e54641–e54641. 1 indexed citations

Ko, Taehoon, et al.. (2024). Self-sovereign management scheme of personal health record with personal data store and decentralized identifier. Computational and Structural Biotechnology Journal. 28. 16–28.

Kim, Hyung Min, Taehoon Ko, Hyoeun Kang, et al.. (2024). Improved prediction of clinical pregnancy using artificial intelligence with enhanced inner cell mass and trophectoderm images. Scientific Reports. 14(1). 3240–3240. 6 indexed citations

Joo, Min Wook, et al.. (2023). Development and Validation of a Convolutional Neural Network Model to Predict a Pathologic Fracture in the Proximal Femur Using Abdomen and Pelvis CT Images of Patients With Advanced Cancer. Clinical Orthopaedics and Related Research. 481(11). 2247–2256.

10.

Lee, Kanghyuck, et al.. (2023). Manufacture of artificial lightweight aggregates recycled from anaerobic digested sewage sludge and process optimization by machine learning modeling techniques. Construction and Building Materials. 399. 132502–132502. 6 indexed citations

11.

Lee, Joonyub, et al.. (2023). Prediction of Cardiovascular Complication in Patients with Newly Diagnosed Type 2 Diabetes Using an XGBoost/GRU-ODE-Bayes-Based Machine-Learning Algorithm. Endocrinology and Metabolism. 39(1). 176–185. 5 indexed citations

12.

Oh, Gyu Chul, Taehoon Ko, Min Ho Lee, et al.. (2022). Estimation of low-density lipoprotein cholesterol levels using machine learning. International Journal of Cardiology. 352. 144–149. 17 indexed citations

13.

Bae, Ye Seul, Yujin Park, Taehoon Ko, et al.. (2021). Development and Pilot-Test of Blockchain-Based MyHealthData Platform. Applied Sciences. 11(17). 8209–8209. 4 indexed citations

14.

Song, Yongsoo, et al.. (2021). Privacy-Oriented Technique for COVID-19 Contact Tracing (PROTECT) Using Homomorphic Encryption: Design and Development Study. Journal of Medical Internet Research. 23(7). e26371–e26371. 16 indexed citations

15.

Bae, Ye Seul, et al.. (2021). Satisfaction and Usability of an Information and Communications Technology–Based System by Clinically Healthy Patients With COVID-19 and Medical Professionals: Cross-sectional Survey and Focus Group Interview Study. JMIR Formative Research. 5(8). e26227–e26227. 9 indexed citations

16.

Bae, Ye Seul, Kyung Hwan Kim, Sae Won Choi, et al.. (2020). Information Technology–Based Management of Clinically Healthy COVID-19 Patients: Lessons From a Living and Treatment Support Center Operated by Seoul National University Hospital. Journal of Medical Internet Research. 22(6). e19938–e19938. 39 indexed citations

17.

Lee, Ki Gang, et al.. (2020). The Experimental Process Design of Artificial Lightweight Aggregates Using an Orthogonal Array Table and Analysis by Machine Learning. Materials. 13(23). 5570–5570. 11 indexed citations

18.

Chang, Jooyoung, Jinho Lee, Ahnul Ha, et al.. (2020). Explaining the Rationale of Deep Learning Glaucoma Decisions with Adversarial Examples. Ophthalmology. 128(1). 78–88. 40 indexed citations

19.

Choi, Sae Won, Taehoon Ko, Ki Jeong Hong, & Kyung Hwan Kim. (2019). Machine Learning-Based Prediction of Korean Triage and Acuity Scale Level in Emergency Department Patients. Healthcare Informatics Research. 25(4). 305–305. 56 indexed citations

20.

Shin, Woo Cheol, et al.. (2019). Transfusion after total knee arthroplasty can be predicted using the machine learning algorithm. Knee Surgery Sports Traumatology Arthroscopy. 28(6). 1757–1764. 68 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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