Byeong‐Cheol Ahn

8.9k total citations · 3 hit papers
274 papers, 6.6k citations indexed

About

Byeong‐Cheol Ahn is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Byeong‐Cheol Ahn has authored 274 papers receiving a total of 6.6k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Molecular Biology, 64 papers in Radiology, Nuclear Medicine and Imaging and 64 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Byeong‐Cheol Ahn's work include Thyroid Cancer Diagnosis and Treatment (59 papers), Extracellular vesicles in disease (40 papers) and Medical Imaging Techniques and Applications (23 papers). Byeong‐Cheol Ahn is often cited by papers focused on Thyroid Cancer Diagnosis and Treatment (59 papers), Extracellular vesicles in disease (40 papers) and Medical Imaging Techniques and Applications (23 papers). Byeong‐Cheol Ahn collaborates with scholars based in South Korea, India and United States. Byeong‐Cheol Ahn's co-authors include Prakash Gangadaran, Jaetae Lee, Shin Young Jeong, Chae Moon Hong, Ji Min Oh, Sang‐Woo Lee, S Kalimuthu, Ramya Lakshmi Rajendran, Ho‐Won Lee and Liya Zhu and has published in prestigious journals such as PLoS ONE, Biomaterials and Scientific Reports.

In The Last Decade

Byeong‐Cheol Ahn

258 papers receiving 6.5k citations

Hit Papers

align trajectories

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.

Exosomes Derived From Natural Killer Cells Exert Therapeutic Effect in Melanoma

2017 385 citations Liya Zhu, S Kalimuthu et al. profile →
Tumor microenvironment signaling and therapeutics in cancer progression

2023 154 citations Anshika Goenka, Fatima Khan et al. profile →
CAR T-Cell-Based gene therapy for cancers: new perspectives, challenges, and clinical developments

2022 122 citations Ramya Lakshmi Rajendran, Fatima Khan et al. profile →

Peers

Countries citing papers authored by Byeong‐Cheol Ahn

Since Specialization

Citations

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

Fields of papers citing papers by Byeong‐Cheol Ahn

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Byeong‐Cheol Ahn. 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 Byeong‐Cheol Ahn. The network helps show where Byeong‐Cheol Ahn may publish in the future.

Co-authorship network of co-authors of Byeong‐Cheol Ahn

This figure shows the co-authorship network connecting the top 25 collaborators of Byeong‐Cheol Ahn. A scholar is included among the top collaborators of Byeong‐Cheol Ahn 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 Byeong‐Cheol Ahn. Byeong‐Cheol Ahn 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

#	Work	Indexed citations
1	Sustainable-biomass-derived multifunctional carbon dots as fluorescent probes for multi-purpose advanced imaging, migration and security solutions 2025 ·Surfaces and Interfaces ·Raji Atchudan, (unknown), Suguna Perumal, Prakash Gangadaran, Ashok K. Sundramoorthy, Devaraj Manoj, Ramya Lakshmi Rajendran, Byeong‐Cheol Ahn, Maqusood Ahamed, Seung Woo Lee	6
2	Noninvasive in vivo imaging of macrophages: understanding tumor microenvironments and delivery of therapeutics 2025 ·Biomarker Research ·Prakash Gangadaran, (unknown), Ramya Lakshmi Rajendran, Anshika Goenka, Ji Min Oh, Fatima Khan, K.N. ArulJothi, Sathish Muthu, Krishnan Anand, Chae Moon Hong, Byeong‐Cheol Ahn	7
3	Natural Killer Cell-Derived Exosome Mimetics as Natural Nanocarriers for In Vitro Delivery of Chemotherapeutics to Thyroid Cancer Cells 2025 ·Experimental Oncology ·Lei Zhu, Byeong‐Cheol Ahn	3
4	Exosomes in Bone Cancer: Unveiling their Vital Role in Diagnosis, Prognosis, and Therapeutic Advancements 2024 ·Journal of Cancer ·(unknown), (unknown), (unknown), Ramya Lakshmi Rajendran, (unknown), Sushmita Sen, (unknown), (unknown), Chae Moon Hong, Prakash Gangadaran, Byeong‐Cheol Ahn, Krishnan Anand	3
5	Clinical Outcomes of Maintenance Durvalumab After Definitive Concurrent Chemoradiotherapy in Unresectable Locally Advanced Stage III NSCLC According to EGFR and ALK Status: Korean Cancer Study Group LU-22-18 2024 ·JTO Clinical and Research Reports ·(unknown), (unknown), Young Saing Kim, Keon Uk Park, Jang Ho Cho, Hong-Sik Kim, Ki Hyeong Lee, (unknown), Il Hwan Kim, Kyung Hee Lee, Gyeong‐Won Lee, Seong Yoon Yi, Byeong‐Cheol Ahn, Min-Young Lee, Hyun Ae Jung, Sehhoon Park, Jong‐Mu Sun, Jin Seok Ahn, Se‐Hoon Lee, Myung‐Ju Ahn	1
6	Unveiling Invisible Extracellular Vesicles: Cutting‐Edge Technologies for Their in Vivo Visualization 2024 ·Wiley Interdisciplinary Reviews Nanomedicine and Nanobiotechnology ·Prakash Gangadaran, Fatima Khan, Ramya Lakshmi Rajendran, (unknown), Anshika Goenka, Byeong‐Cheol Ahn	8
7	Extracellular vesicle mimetics engineered from mesenchymal stem cells and curcumin promote fibrosis regression in a mouse model of thioacetamide-induced liver fibrosis 2024 ·Regenerative Therapy ·Arunnehru Gopal, Prakash Gangadaran, Ramya Lakshmi Rajendran, Ji Min Oh, Ho‐Won Lee, Chae Moon Hong, S Kalimuthu, Man‐Hoon Han, Jaetae Lee, Byeong‐Cheol Ahn	5
8	Alzheimer’s Disease Pathology and Assistive Nanotheranostic Approaches for Its Therapeutic Interventions 2024 ·International Journal of Molecular Sciences ·(unknown), (unknown), Ramya Lakshmi Rajendran, (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), Krishnan Anand, Byeong‐Cheol Ahn, Prakash Gangadaran	5
9	Cannabidiol for musculoskeletal regenerative medicine 2023 ·Experimental Biology and Medicine ·Gabriel Ohana Marques Azzini, (unknown), Gabriel Silva Santos, (unknown), (unknown), (unknown), Ansar Mahmood, (unknown), Madhan Jeyaraman, Arulkumar Nallakumarasamy, Naveen Jeyaraman, Lucas Furtado da Fonseca, (unknown), Rodrigo Santamaría, (unknown), Prakash Gangadaran, Byeong‐Cheol Ahn, José Fábio Lana	8
10	Reliability of Alkaline Phosphatase for Differentiating Flare Phenomenon from Disease Progression with Bone Scintigraphy 2022 ·Cancers ·Ji‐hoon Jung, Chae Moon Hong, (unknown), (unknown), Sang‐Woo Lee, Jaetae Lee, Byeong‐Cheol Ahn	7
11	Deep Neural Network Models for Colon Cancer Screening 2022 ·Cancers ·Muthu Subash Kavitha, Prakash Gangadaran, (unknown), Balu Alagar Venmathi Maran, Takio Kurita, Byeong‐Cheol Ahn	26
12	Application of Sygen® in Diabetic Peripheral Neuropathies—A Review of Biological Interactions 2022 ·Bioengineering ·(unknown), Madhan Jeyaraman, Naveen Jeyaraman, Ramya Lakshmi Rajendran, (unknown), (unknown), Gabriel Silva Santos, (unknown), (unknown), Lucas Furtado da Fonseca, (unknown), Prakash Gangadaran, Byeong‐Cheol Ahn, José Fábio Lana	2
13	Author Correction: Deep learning enables automated localization of the metastatic lymph node for thyroid cancer on 131I post-ablation whole-body planar scans 2020 ·Scientific Reports ·Muthu Subash Kavitha, Changhee Lee, (unknown), Takio Kurita, Byeong‐Cheol Ahn	2
14	Deep learning enables automated localization of the metastatic lymph node for thyroid cancer on 131I post-ablation whole-body planar scans 2020 ·Scientific Reports ·Muthu Subash Kavitha, Changhee Lee, (unknown), Takio Kurita, Byeong‐Cheol Ahn	13
15	In Vivo Tracking of Chemokine Receptor CXCR4-Engineered Mesenchymal Stem Cell Migration by Optical Molecular Imaging 2017 ·Stem Cells International ·S Kalimuthu, Ji Min Oh, Prakash Gangadaran, Liya Zhu, Ho‐Won Lee, Ramya Lakshmi Rajendran, Se Hwan Baek, Yong Hyun Jeon, Shin Young Jeong, Sang‐Woo Lee, Jaetae Lee, Byeong‐Cheol Ahn	59
16	Deep vector-based convolutional neural network approach for automatic recognition of colonies of induced pluripotent stem cells 2017 ·PLoS ONE ·Muthu Subash Kavitha, Takio Kurita, Soon-Yong Park, Sung‐Il Chien, Jae‐sung Bae, Byeong‐Cheol Ahn	34
17	Estimation of External Radiation Dose to Caregivers of Patients Treated with Radioiodine after Thyroidectomy 2014 ·Health Physics ·(unknown), Jae Won Jung, (unknown), Byeong‐Cheol Ahn, (unknown), (unknown), (unknown), (unknown)	14
18	Usefulness of F-18 FDG PET/CT in Adrenal Incidentaloma: Differential Diagnosis of Adrenal Metastasis in Oncologic Patients 2009 ·Nuclear Medicine and Molecular Imaging ·(unknown), Bong‐Il Song, Sungmin Kang, (unknown), (unknown), Sang‐Woo Lee, Jeongsoo Yoo, Byeong‐Cheol Ahn, Jaetae Lee	3
19	Assessment of Bone Metastasis using Nuclear Medicine Imaging in Breast Cancer : Comparison between PET/CT and Bone Scan 2007 ·Nuclear Medicine and Molecular Imaging ·(unknown), Byeong‐Cheol Ahn, Sungmin Kang, (unknown), Jinho Bae, Sang-Woo Lee, (unknown), Jeongsoo Yoo, Ho‐Young Park, Jaetae Lee	0
20	Detection of Multidrug Resistance Using Molecular Nuclear Technique 2004 ·The Korean Journal of Nuclear Medicine ·Jaetae Lee, Byeong‐Cheol Ahn	0

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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