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Sung Soo Kim

London School of Hygiene & Tropical Medicine · GB
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Area of research
Ophthalmology · Radiology, Nuclear Medicine and Imaging
Research interest
Research focused on Disease and Biomarker, with related work in Retinal, Hazard ratio, Biobank. Notable publications include 'Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes', 'Retinal photograph-based deep learning predicts biological age, and stratifies morbidity and mortality risk', and 'Robust Identification of Alzheimer’s Disease subtypes based on cortical atrophy patterns'.
h-index
citations
876
works
9
NIH funding
primary concept
email

Recent publications

Prognostic potentials of AI in ophthalmology: systemic disease forecasting via retinal imaging
Eye and Vision 2024cited by 37position: middledoi
Validation of a deep-learning-based retinal biomarker (Reti-CVD) in the prediction of cardiovascular disease: data from UK Biobank
BMC Medicine 2023cited by 54position: middledoi
Cardiovascular disease risk assessment using a deep-learning-based retinal biomarker: a comparison with existing risk scores
European Heart Journal - Digital Health 2023cited by 35position: middledoi
Pivotal trial of a deep-learning-based retinal biomarker (Reti-CVD) in the prediction of cardiovascular disease: data from CMERC-HI
Journal of the American Medical Informatics Association 2023cited by 35position: middledoi
Retinal photograph-based deep learning predicts biological age, and stratifies morbidity and mortality risk
Age and Ageing 2022cited by 91position: middledoi
Detection of features associated with neovascular age-related macular degeneration in ethnically distinct data sets by an optical coherence tomography: trained deep learning algorithm
British Journal of Ophthalmology 2020cited by 42position: middledoi
Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes
Nature Genetics 2018cited by 468position: middledoi
Robust Identification of Alzheimer’s Disease subtypes based on cortical atrophy patterns
Scientific Reports 2017cited by 83position: middledoi
Highlighting the evidence gap: how cost-effective are interventions to improve early childhood nutrition and development?
Health Policy and Planning 2014cited by 31position: middledoi

Grants

No grants ingested yet.

Frequent collaborators

Tyler Hyungtaek Rim · National University of Singapore6 papers (2020–2024)Yih Chung Tham · National University of Singapore6 papers (2020–2024)Sungha Park · Keimyung University5 papers (2022–2024)Ching‐Yu Cheng · Tsinghua University5 papers (2022–2024) · 5 papers (2020–2023) · 5 papers (2022–2024)Marco Yu · Wenzhou Medical University4 papers (2022–2023)Tien Yin Wong · Neuroscience Research Australia4 papers (2020–2023) · 3 papers (2022–2024)Joseph Yi · The University of Texas Health Science Center at Houston3 papers (2023–2023)Qingsheng Peng · National University of Singapore2 papers (2023–2024) · 2 papers (2023–2023)Simon Nusinovici · National University of Singapore2 papers (2022–2023) · 2 papers (2023–2023)Zhi Da Soh · National University of Singapore2 papers (2022–2024) · 2 papers (2023–2024)Gregory Y.H. Lip · Medical University of Białystok2 papers (2023–2023)Eduard Shantsila · University of Liverpool2 papers (2023–2023)Paul Leeson · John Radcliffe Hospital2 papers (2023–2023)Hyeon Chang Kim · Institute of Liver and Biliary Sciences2 papers (2022–2023)
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