Hojin Moon

839 total citations
34 papers, 602 citations indexed

About

Hojin Moon is a scholar working on Molecular Biology, Artificial Intelligence and Statistics and Probability. According to data from OpenAlex, Hojin Moon has authored 34 papers receiving a total of 602 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 9 papers in Artificial Intelligence and 9 papers in Statistics and Probability. Recurrent topics in Hojin Moon's work include Gene expression and cancer classification (9 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Diabetic Foot Ulcer Assessment and Management (4 papers). Hojin Moon is often cited by papers focused on Gene expression and cancer classification (9 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Diabetic Foot Ulcer Assessment and Management (4 papers). Hojin Moon collaborates with scholars based in United States, Taiwan and South Korea. Hojin Moon's co-authors include Hongshik Ahn, Ralph L. Kodell, James J. Chen, Songjoon Baek, Hyunjoong Kim, Hongshik Ahn, Noha Lim, Melissa Fazzari, Chun‐Houh Chen and Chen‐An Tsai and has published in prestigious journals such as SHILAP Revista de lepidopterología, Cancer Research and Endocrinology.

In The Last Decade

Hojin Moon

33 papers receiving 578 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hojin Moon United States	12	193	156	76	71	63	34	602
Blaise Hanczar France	17	342 1.8×	359 2.3×	112 1.5×	37 0.5×	53 0.8×	39	934
Marcel Brun United States	17	223 1.2×	430 2.8×	100 1.3×	39 0.5×	23 0.4×	59	882
Guzmán Santafé Spain	8	273 1.4×	378 2.4×	49 0.6×	26 0.4×	20 0.3×	16	914
Zheng Chen China	11	106 0.5×	94 0.6×	49 0.6×	36 0.5×	65 1.0×	63	700
Alexis Boukouvalas United Kingdom	12	93 0.5×	161 1.0×	49 0.6×	21 0.3×	21 0.3×	23	594
Umesh Gupta India	17	113 0.6×	76 0.5×	33 0.4×	26 0.4×	49 0.8×	71	954
Yuan‐chin Ivan Chang Taiwan	15	137 0.7×	108 0.7×	26 0.3×	45 0.6×	124 2.0×	46	517
Miriam Seoane Santos Portugal	11	479 2.5×	72 0.5×	68 0.9×	12 0.2×	47 0.7×	24	835
Reshad Hosseini Iran	15	271 1.4×	190 1.2×	267 3.5×	23 0.3×	43 0.7×	48	764
Cheng Ju China	15	153 0.8×	85 0.5×	83 1.1×	18 0.3×	126 2.0×	37	704

Countries citing papers authored by Hojin Moon

Since Specialization

Citations

This map shows the geographic impact of Hojin Moon'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 Hojin Moon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hojin Moon more than expected).

Fields of papers citing papers by Hojin Moon

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hojin Moon. 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 Hojin Moon. The network helps show where Hojin Moon may publish in the future.

Co-authorship network of co-authors of Hojin Moon

This figure shows the co-authorship network connecting the top 25 collaborators of Hojin Moon. A scholar is included among the top collaborators of Hojin Moon 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 Hojin Moon. Hojin Moon 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

Moon, Hojin, et al.. (2024). Prediction of Treatment Recommendations Via Ensemble Machine Learning Algorithms for Non-Small Cell Lung Cancer Patients in Personalized Medicine. Cancer Informatics. 23. 2683898957–2683898957. 2 indexed citations

Moon, Hojin, et al.. (2019). Identification of Risk Factors and Likelihood of Benefit from Adjuvant Chemotherapy for Early Stage Lung Cancer Patients. Journal of Biopharmaceutical Statistics. 30(3). 430–444. 3 indexed citations

Strauss, Michael B., et al.. (2018). Clinical Applications and Validation of an Innovative Wound Score.. PubMed. 30(6). 154–159.

Moon, Hojin, Hongshik Ahn, & Ralph L. Kodell. (2015). A Computational Tool for Testing Dose-related Trend Using an Age-adjusted Bootstrap-based Poly-k Test. SHILAP Revista de lepidopterología. 1 indexed citations

Moon, Hojin. (2014). 3D Printing of the wind instruments. 105–118. 2 indexed citations

Moon, Hojin, Steven Kim, James J. Chen, Nysia I. George, & Ralph L. Kodell. (2012). Model Uncertainty and Model Averaging in the Estimation of Infectious Doses for Microbial Pathogens. Risk Analysis. 33(2). 220–231. 10 indexed citations

Kim, Woo‐Young, Mi-Jung Kim, Hojin Moon, et al.. (2011). Differential Impacts of Insulin-Like Growth Factor-Binding Protein-3 (IGFBP-3) in Epithelial IGF-Induced Lung Cancer Development. Endocrinology. 152(6). 2164–2173. 19 indexed citations

Kim, Hyunjoong, et al.. (2011). A weight-adjusted voting algorithm for ensembles of classifiers. Journal of the Korean Statistical Society. 40(4). 437–449. 94 indexed citations

Young, John F., Richard H. Luecke, Bruce A. Pearce, et al.. (2009). Human Organ/Tissue Growth Algorithms that Include Obese Individuals and Black/White Population Organ Weight Similarities from Autopsy Data. Journal of Toxicology and Environmental Health. 72(8). 527–540. 53 indexed citations

10.

Lim, Noha, Hongshik Ahn, Hojin Moon, & James J. Chen. (2009). Classification of High-Dimensional Data with Ensemble of Logistic Regression Models. Journal of Biopharmaceutical Statistics. 20(1). 160–171. 13 indexed citations

11.

Kodell, Ralph L., Bruce A. Pearce, Songjoon Baek, et al.. (2008). A model-free ensemble method for class prediction with application to biomedical decision making. Artificial Intelligence in Medicine. 46(3). 267–276. 12 indexed citations

12.

Melis, Joost P.M., S. Wijnhoven, Rudolf B. Beems, et al.. (2008). Mouse Models for Xeroderma Pigmentosum Group A and Group C Show Divergent Cancer Phenotypes. Cancer Research. 68(5). 1347–1353. 51 indexed citations

13.

Ahn, Hongshik, Hojin Moon, Melissa Fazzari, et al.. (2007). Classification by ensembles from random partitions of high-dimensional data. Computational Statistics & Data Analysis. 51(12). 6166–6179. 70 indexed citations

14.

Moon, Hojin, et al.. (2007). Ensemble methods for classification of patients for personalized medicine with high-dimensional data. Artificial Intelligence in Medicine. 41(3). 197–207. 67 indexed citations

15.

Ahn, Hongshik, et al.. (2006). A dose–response test via closed‐form solutions for constrained MLEs in survival/sacrifice experiments. Statistics in Medicine. 26(3). 694–708. 1 indexed citations

16.

Moon, Hojin, et al.. (2006). Classification methods for the development of genomic signatures from high-dimensional data.. Genome Biology. 7(12). R121–R121. 14 indexed citations

17.

Tsai, Chen‐An, et al.. (2006). Decision threshold adjustment in class prediction. SAR and QSAR in environmental research. 17(3). 337–352. 65 indexed citations

18.

Chen, James J., Hojin Moon, & Ralph L. Kodell. (2006). A probabilistic framework for non-cancer risk assessment. Regulatory Toxicology and Pharmacology. 48(1). 45–50. 10 indexed citations

19.

Moon, Hojin, Hyun‐Joo Kim, James J. Chen, & Ralph L. Kodell. (2005). Model Averaging Using the Kullback Information Criterion in Estimating Effective Doses for Microbial Infection and Illness. Risk Analysis. 25(5). 1147–1159. 36 indexed citations

20.

Fuhrmann, Daniel R., Anuj Srivastava, & Hojin Moon. (2002). Subspace tracking via rigid body dynamics. 578–581. 6 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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