Jae Ho Sohn

4.0k total citations · 2 hit papers
64 papers, 2.1k citations indexed

About

Jae Ho Sohn is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Hepatology. According to data from OpenAlex, Jae Ho Sohn has authored 64 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Radiology, Nuclear Medicine and Imaging, 16 papers in Biomedical Engineering and 11 papers in Hepatology. Recurrent topics in Jae Ho Sohn's work include Radiomics and Machine Learning in Medical Imaging (13 papers), Hepatocellular Carcinoma Treatment and Prognosis (10 papers) and Odor and Emission Control Technologies (9 papers). Jae Ho Sohn is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (13 papers), Hepatocellular Carcinoma Treatment and Prognosis (10 papers) and Odor and Emission Control Technologies (9 papers). Jae Ho Sohn collaborates with scholars based in United States, South Korea and Australia. Jae Ho Sohn's co-authors include Michael Atzeni, Youngho Seo, Hari Trivedi, Kwang-Nam Jin, Sunggyun Park, Eui Jin Hwang, Sangheum Hwang, Jin Mo Goo, Kun Young Lim and Chang Min Park and has published in prestigious journals such as Scientific Reports, Radiology and International Journal of Molecular Sciences.

In The Last Decade

Jae Ho Sohn

63 papers receiving 2.0k citations

Hit Papers

Development and Validatio... 2018 2026 2020 2023 2018 2018 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Development and Validation of Deep Learning–based Automatic Detection Algorithm for Malignant Pulmonary Nodules on Chest Radiographs
    2018 382 citations Jae Ho Sohn et al. Radiology profile →
  2. A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18F-FDG PET of the Brain
    2018 379 citations Yiming Ding, Jae Ho Sohn et al. Radiology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jae Ho Sohn United States 24 832 448 327 311 262 64 2.1k
Yukihiro Nomura Japan 25 434 0.5× 179 0.4× 442 1.4× 191 0.6× 85 0.3× 204 2.0k
Xuhong Hou China 33 784 0.9× 64 0.1× 164 0.5× 200 0.6× 58 0.2× 94 3.5k
Pu Wang China 19 824 1.0× 102 0.2× 778 2.4× 455 1.5× 199 0.8× 69 2.4k
Kyunga Kim South Korea 30 471 0.6× 132 0.3× 709 2.2× 97 0.3× 46 0.2× 289 4.2k
Zhiyuan Wu China 22 339 0.4× 106 0.2× 203 0.6× 225 0.7× 24 0.1× 107 1.9k
Wenxing Li China 21 231 0.3× 90 0.2× 205 0.6× 161 0.5× 36 0.1× 163 2.0k
Yi Shi China 29 114 0.1× 321 0.7× 325 1.0× 96 0.3× 50 0.2× 136 2.8k
Mohammad Mirza‐Aghazadeh‐Attari Iran 19 218 0.3× 109 0.2× 123 0.4× 81 0.3× 37 0.1× 96 1.4k
Hyun Jung Koo South Korea 26 852 1.0× 299 0.7× 572 1.7× 72 0.2× 29 0.1× 167 2.9k

Countries citing papers authored by Jae Ho Sohn

Since Specialization
Citations

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

Fields of papers citing papers by Jae Ho Sohn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jae Ho Sohn. 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 Jae Ho Sohn. The network helps show where Jae Ho Sohn may publish in the future.

Co-authorship network of co-authors of Jae Ho Sohn

This figure shows the co-authorship network connecting the top 25 collaborators of Jae Ho Sohn. A scholar is included among the top collaborators of Jae Ho Sohn 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 Jae Ho Sohn. Jae Ho Sohn is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Brandman, Danielle, et al.. (2023). Underrecognition and Suboptimal Quality of Care for Nonalcoholic Fatty Liver Disease Cirrhosis in Primary Care Patients with Diabetes Mellitus. The American Journal of Medicine. 137(2). 172–177.e2. 4 indexed citations
2.
Chaudhari, Gunvant, Timothy L. Chen, Gabby B. Joseph, et al.. (2022). Application of a Domain-specific BERT for Detection of Speech Recognition Errors in Radiology Reports. Radiology Artificial Intelligence. 4(4). e210185–e210185. 9 indexed citations
3.
Sohn, Jae Ho, Yixin Chen, Dmytro Lituiev, et al.. (2022). Prediction of future healthcare expenses of patients from chest radiographs using deep learning: a pilot study. Scientific Reports. 12(1). 8344–8344. 4 indexed citations
4.
Sohn, Jae Ho, Spencer C. Behr, Miguel Hernandez Pampaloni, & Youngho Seo. (2021). Quantitative Assessment of Myocardial Ischemia With Positron Emission Tomography. Journal of Thoracic Imaging. 38(4). 247–259. 2 indexed citations
5.
Joseph, Gabby B., Charles E. McCulloch, Jae Ho Sohn, et al.. (2021). AI MSK clinical applications: cartilage and osteoarthritis. Skeletal Radiology. 51(2). 331–343. 24 indexed citations
6.
Seo, Youngho, et al.. (2021). High precision localization of pulmonary nodules on chest CT utilizing axial slice number labels. BMC Medical Imaging. 21(1). 66–66. 4 indexed citations
7.
Schacky, Claudio E. von, Jae Ho Sohn, Felix Liu, et al.. (2020). Development and Validation of a Multitask Deep Learning Model for Severity Grading of Hip Osteoarthritis Features on Radiographs. Radiology. 295(1). 136–145. 75 indexed citations
8.
Schacky, Claudio E. von, Jae Ho Sohn, Sarah C. Foreman, et al.. (2020). Development and performance comparison with radiologists of a multitask deep learning model for severity grading of hip osteoarthritis features on radiographs. Osteoarthritis and Cartilage. 28. S306–S308. 4 indexed citations
9.
Sohn, Jae Ho, Stanley Chun-Wei Lee, Amie Y. Lee, et al.. (2020). An Open-Source, Vender Agnostic Hardware and Software Pipeline for Integration of Artificial Intelligence in Radiology Workflow. Journal of Digital Imaging. 33(4). 1041–1046. 28 indexed citations
10.
Schacky, Claudio E. von, F. Liu, Sarah C. Foreman, et al.. (2019). Automated severity grading of radiographic hip osteoarthritis features with deep learning. Osteoarthritis and Cartilage. 27. S396–S397. 1 indexed citations
11.
Trivedi, Hari, Maryam Panahiazar, Dmytro Lituiev, et al.. (2018). Large Scale Semi-Automated Labeling of Routine Free-Text Clinical Records for Deep Learning. Journal of Digital Imaging. 32(1). 30–37. 17 indexed citations
12.
Ding, Yiming, Jae Ho Sohn, Michael Kawczynski, et al.. (2018). A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18F-FDG PET of the Brain. Radiology. 290(2). 456–464. 379 indexed citations breakdown →
13.
Fleckenstein, Florian Nima, Rüdiger Schernthaner, Rafael Durán, et al.. (2016). 3D Quantitative tumour burden analysis in patients with hepatocellular carcinoma before TACE: comparing single-lesion vs. multi-lesion imaging biomarkers as predictors of patient survival. European Radiology. 26(9). 3243–3252. 25 indexed citations
14.
15.
Fleckenstein, Florian Nima, Rüdiger Schernthaner, Rafael Durán, et al.. (2016). Renal Cell Carcinoma Metastatic to the Liver: Early Response Assessment after Intraarterial Therapy Using 3D Quantitative Tumor Enhancement Analysis. Translational Oncology. 9(5). 377–383. 9 indexed citations
16.
Schernthaner, Ruediger E., Reham R. Haroun, Rafael Durán, et al.. (2016). Improved Visibility of Metastatic Disease in the Liver During Intra-Arterial Therapy Using Delayed Arterial Phase Cone-Beam CT. CardioVascular and Interventional Radiology. 39(10). 1429–1437. 16 indexed citations
17.
Durán, Rafael, Jae Ho Sohn, Rüdiger Schernthaner, et al.. (2015). Radiologic-pathologic analysis of quantitative 3D tumour enhancement on contrast-enhanced MR imaging: a study of ROI placement. European Radiology. 26(1). 103–113. 28 indexed citations
18.
19.
Sohn, Jae Ho, Richard M. Stuetz, & Michael Atzeni. (2010). Non-specific chemical gas sensor arrays for environmental monitoring of odour emissions: a review. University of Southern Queensland ePrints (University of Southern Queensland).
20.
Hudson, N., et al.. (2007). Assessing the medium-term impact of permeable pond covers on pond performance and odour management. Queensland Department of Agriculture and Fisheries archive of scientific and research publications (Queensland Department of Agriculture and Fisheries). 1 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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