Sang-Il Oh

608 total citations
15 papers, 410 citations indexed

About

Sang-Il Oh is a scholar working on Pulmonary and Respiratory Medicine, Computer Vision and Pattern Recognition and Oncology. According to data from OpenAlex, Sang-Il Oh has authored 15 papers receiving a total of 410 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Pulmonary and Respiratory Medicine, 5 papers in Computer Vision and Pattern Recognition and 5 papers in Oncology. Recurrent topics in Sang-Il Oh's work include Video Surveillance and Tracking Methods (4 papers), Colorectal Cancer Screening and Detection (4 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Sang-Il Oh is often cited by papers focused on Video Surveillance and Tracking Methods (4 papers), Colorectal Cancer Screening and Detection (4 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Sang-Il Oh collaborates with scholars based in South Korea and Japan. Sang-Il Oh's co-authors include Hang-Bong Kang, Jeong‐Won Park, Shinae Lee, Yooseok Shin, Young Hoon Youn, Hyojin Park, Jaeyoung Chun, Jie‐Hyun Kim, In Gyu Kwon and Seung Ho Choi and has published in prestigious journals such as PLoS ONE, Scientific Reports and Sensors.

In The Last Decade

Sang-Il Oh

14 papers receiving 393 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sang-Il Oh South Korea 8 128 106 103 86 78 15 410
Sophia Bano United Kingdom 12 32 0.3× 49 0.5× 43 0.4× 62 0.7× 157 2.0× 44 412
Yeong-Gil Shin South Korea 13 79 0.6× 220 2.1× 151 1.5× 12 0.1× 155 2.0× 53 495
Federico Bolelli Italy 13 23 0.2× 96 0.9× 84 0.8× 65 0.8× 200 2.6× 37 462
Christian Jaremenko Germany 8 19 0.1× 92 0.9× 38 0.4× 16 0.2× 31 0.4× 12 355
Adam Piórkowski Poland 14 76 0.6× 142 1.3× 41 0.4× 5 0.1× 94 1.2× 78 493
Jiapan Guo Netherlands 11 68 0.5× 163 1.5× 99 1.0× 11 0.1× 37 0.5× 25 368
Byoung-Dai Lee South Korea 12 64 0.5× 200 1.9× 66 0.6× 14 0.2× 104 1.3× 51 501
Mohd Ezane Aziz Malaysia 13 73 0.6× 57 0.5× 66 0.6× 18 0.2× 101 1.3× 43 499

Countries citing papers authored by Sang-Il Oh

Since Specialization
Citations

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

Fields of papers citing papers by Sang-Il Oh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sang-Il Oh. 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 Sang-Il Oh. The network helps show where Sang-Il Oh may publish in the future.

Co-authorship network of co-authors of Sang-Il Oh

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

All Works

15 of 15 papers shown
1.
Kang, Dong Hoon, Jie‐Hyun Kim, Sang-Il Oh, et al.. (2025). Enhancing Lymph Node Metastasis Risk Prediction in Early Gastric Cancer Through the Integration of Endoscopic Images and Real-World Data in a Multimodal AI Model. Cancers. 17(5). 869–869. 1 indexed citations
2.
3.
Kim, Hyojune, Seung Min Ryu, Sang-Il Oh, et al.. (2024). Clinical validation of enhanced CT imaging for distal radius fractures through conditional Generative Adversarial Networks (cGAN). PLoS ONE. 19(8). e0308346–e0308346. 4 indexed citations
4.
Yong, Seung Hyun, Sang Hoon Lee, Sang-Il Oh, et al.. (2022). Malignant thoracic lymph node classification with deep convolutional neural networks on real-time endobronchial ultrasound (EBUS) images. Translational Lung Cancer Research. 11(1). 14–23. 12 indexed citations
5.
Kim, Jie‐Hyun, Sang-Il Oh, Kyung‐Nam Kim, et al.. (2022). An Optimal Artificial Intelligence System for Real-Time Endoscopic Prediction of Invasion Depth in Early Gastric Cancer. Cancers. 14(23). 6000–6000. 12 indexed citations
6.
Lee, Shinae, et al.. (2021). Deep learning for early dental caries detection in bitewing radiographs. Scientific Reports. 11(1). 16807–16807. 109 indexed citations
7.
Yoon, Hong Jin, Seung Up Kim, Jie‐Hyun Kim, et al.. (2019). A Lesion-Based Convolutional Neural Network Improves Endoscopic Detection and Depth Prediction of Early Gastric Cancer. Journal of Clinical Medicine. 8(9). 1310–1310. 123 indexed citations
8.
Oh, Sang-Il & Hang-Bong Kang. (2018). Development and utilization of a disgusting image dataset to understand and predict visual disgust. Image and Vision Computing. 72. 24–38. 1 indexed citations
9.
Oh, Sang-Il & Hang-Bong Kang. (2017). Multiple Objects Fusion Tracker Using a Matching Network for Adaptively Represented Instance Pairs. Sensors. 17(4). 883–883. 3 indexed citations
10.
Oh, Sang-Il & Hang-Bong Kang. (2017). Object Detection and Classification by Decision-Level Fusion for Intelligent Vehicle Systems. Sensors. 17(1). 207–207. 84 indexed citations
11.
Oh, Sang-Il & Hang-Bong Kang. (2017). A new object proposal generation method for object detection in RGB-D data. 393–398. 2 indexed citations
12.
Oh, Sang-Il & Hang-Bong Kang. (2016). Fast Occupancy Grid Filtering Using Grid Cell Clusters From LIDAR and Stereo Vision Sensor Data. IEEE Sensors Journal. 16(19). 7258–7266. 27 indexed citations
13.
14.
Suzuki, Kazuya, Mariko Fukui, Yoshitaka Kitamura, et al.. (2013). The presence of air bronchogram is a novel predictor of negative nodal involvement in radiologically pure-solid lung cancer. European Journal of Cardio-Thoracic Surgery. 45(4). 699–702. 20 indexed citations
15.
Takamochi, Kazuya, Sang-Il Oh, & Kazuyuki Suzuki. (2010). Prognostic Evaluation of Nodal Staging Based on the New IASLC Lymph Node Map for Lung Cancer. The Thoracic and Cardiovascular Surgeon. 58(6). 345–349. 8 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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2026