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Hyunsoo Yoon - Publications

Affiliations: 
2018 Arizona State University, Tempe, AZ, United States 
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18 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2024 Li J, Wang H, Argenziano M, Yoon H, Boyett D, Save A, Petridis P, Savage W, Jackson P, Hawkins-Daarud A, Tran N, Hu L, Al-Dalahmah O, Bruce J, Grinband J, et al. Biologically-informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post-treatment glioblastoma. Research Square. PMID 38585856 DOI: 10.21203/rs.3.rs-3891425/v1  0.377
2023 Yoon H, Schwedt TJ, Chong CD, Olatunde O, Wu T. Harmonizing Healthy Cohorts to Support Multicenter Studies on Migraine Classification using Brain MRI Data. Medrxiv : the Preprint Server For Health Sciences. PMID 37425905 DOI: 10.1101/2023.06.26.23291909  0.345
2021 Yoon H, Gaw N. A novel multi-task linear mixed model for smartphone-based telemonitoring Expert Systems With Applications. 164: 113809. DOI: 10.1016/J.Eswa.2020.113809  0.626
2020 Gao F, Yoon H, Xu Y, Goradia D, Luo J, Wu T, Su Y. AD-NET: Age-adjust neural network for improved MCI to AD conversion prediction. Neuroimage. Clinical. 27: 102290. PMID 32570205 DOI: 10.1016/J.Nicl.2020.102290  0.376
2020 Setzer FC, Shi KJ, Zhang Z, Yan H, Yoon H, Mupparapu M, Li J. Artificial Intelligence for the Computer-aided Detection of Periapical Lesions in Cone-beam Computed Tomographic Images. Journal of Endodontics. PMID 32402466 DOI: 10.1016/J.Joen.2020.03.025  0.333
2020 Gao F, Yoon H, Wu T, Chu X. A Feature Transfer Enabled Multi-Task Deep Learning Model on Medical Imaging Expert Systems With Applications. 143: 112957. DOI: 10.1016/J.Eswa.2019.112957  0.396
2019 Gaw N, Hawkins-Daarud A, Hu LS, Yoon H, Wang L, Xu Y, Jackson PR, Singleton KW, Baxter LC, Eschbacher J, Gonzales A, Nespodzany A, Smith K, Nakaji P, Mitchell JR, et al. Integration of machine learning and mechanistic models accurately predicts variation in cell density of glioblastoma using multiparametric MRI. Scientific Reports. 9: 10063. PMID 31296889 DOI: 10.1038/S41598-019-46296-4  0.632
2019 Gao F, Wu T, Chu X, Yoon H, Xu Y, Patel B. Deep Residual Inception Encoder-Decoder Network for Medical Imaging Synthesis. Ieee Journal of Biomedical and Health Informatics. PMID 31021777 DOI: 10.1109/Jbhi.2019.2912659  0.385
2019 Hu LS, Yoon H, Eschbacher JM, Baxter LC, Dueck AC, Nespodzany A, Smith KA, Nakaji P, Xu Y, Wang L, Karis JP, Hawkins-Daarud AJ, Singleton KW, Jackson PR, Anderies BJ, et al. Accurate Patient-Specific Machine Learning Models of Glioblastoma Invasion Using Transfer Learning. Ajnr. American Journal of Neuroradiology. PMID 30819771 DOI: 10.3174/Ajnr.A5981  0.512
2019 Yoon H, Li J. A Novel Positive Transfer Learning Approach for Telemonitoring of Parkinson’s Disease Ieee Transactions On Automation Science and Engineering. 16: 180-191. DOI: 10.1109/Tase.2018.2874233  0.464
2019 Yoon H, Hawkins-Daarud A, Save A, Singleton K, Clark-Swanson K, Wang L, Bendok B, Mrugala M, Wu T, Bruce J, Hu L, Li J, Canoll PD, Swanson K. NIMG-61. USING MACHINE LEARNING TO BUILD RADIOMICS MODELS THAT DISTINGUISH REGIONS OF GLIOBLASTOMA RECURRENCE VS TUMOR PROGRESSION ON MRI Neuro-Oncology. 21: vi175-vi175. DOI: 10.1093/Neuonc/Noz175.730  0.492
2019 Wang L, Yoon H, Hawkins-Daarud A, Singleton K, Clark-Swanson K, Smith K, Nakaji P, Eschbacher J, Baxter L, Gonzalez A, Nespodzany A, Bendok B, Patra D, De Leon G, Zimmerman R, et al. NIMG-52. UNCERTAINTY QUANTIFICATION IN RADIOMICS Neuro-Oncology. 21: vi172-vi173. DOI: 10.1093/Neuonc/Noz175.721  0.536
2019 Hawkins-Daarud A, Yoon H, Monie D, Singleton K, Ranjbar S, Tran N, Badie B, Rockne R, Brown CE, Hu L, Bruce J, Canoll PD, Li J, Swanson K. Nimg-39. Revealing The Tumor-Immune Landscape Through Spatially-Resolved Radiomics: Case Studies Neuro-Oncology. 21. DOI: 10.1093/Neuonc/Noz175.709  0.301
2019 Wang L, Yoon H, Hawkins-Daarud A, Singleton K, Clark-Swanson K, Bendok B, Mrugala M, Eschbacher J, Smith K, Nakaji P, Gonzalez A, Nespodzany A, Baxter L, Wu T, Swanson K, et al. NIMG-30. REPRODUCIBLE RADIOMIC MAPPING OF TUMOR CELL DENSITY BY MACHINE LEARNING AND DOMAIN ADAPTATION Neuro-Oncology. 21: vi167-vi167. DOI: 10.1093/Neuonc/Noz175.700  0.468
2019 Save A, Hollon T, Farooq Z, Boyett D, Hawkins-Daarud A, Yoon H, Singleton K, Clark-Swanson K, Li J, Swanson K, Freudiger C, Orringer D, Lassman A, Sims P, Grinband J, et al. TMOD-14. RADIOGRAPHIC, STIMULATED RAMAN HISTOLOGIC, AND MULTIPLEXED RNA-SEQUENCING ANALYSIS OF POST-TREATMENT RECURRENT HIGH-GRADE GLIOMAS Neuro-Oncology. 21: vi265-vi265. DOI: 10.1093/Neuonc/Noz175.1113  0.447
2018 Hu L, Gaw N, Yoon H, Eschbacher J, C. Baxter L, A. Smith K, Nakaji P, P. Karis J, Whitmire P, Hawkins-Daarud A, Singleton K, Jackson P, Christine Massey S, Bendok B, Mitchell J, et al. NIMG-12. RADIOGENOMICS ON VENUS AND MARS: IMPACT OF SEX-DIFFERENCES ON MRI AND GENETIC CORRELATIONS IN GLIOBLASTOMA Neuro-Oncology. 20: vi178-vi178. DOI: 10.1093/Neuonc/Noy148.739  0.587
2017 Hu L, Yoon H, Eschbacher J, Baxter L, Smith K, Nakaji P, Mcgee S, Dueck A, Quarles C, Karis J, Hawkins-Daarud A, Jackson P, Massey S, Wu T, Swanson K, et al. NIMG-68. ACCURATE PATIENT-SPECIFIC MACHINE LEARNING MODELS OF GLIOBLASTOMA INVASION USING TRANSFER LEARNING Neuro-Oncology. 19: vi157-vi158. DOI: 10.1093/Neuonc/Nox168.641  0.412
2013 Yoon H, Park C, Kim JS, Baek J. Algorithm learning based neural network integrating feature selection and classification Expert Systems With Applications. 40: 231-241. DOI: 10.1016/J.Eswa.2012.07.018  0.334
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