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Computer Science

D-Index
59
Citations
12950
World Ranking
3446
National Ranking
58

Overview

Mong Li Lee is affiliated with the National University of Singapore, Singapore. Their work spans the fields of Medicine and Computer Science, with a notable focus on Artificial Intelligence and its applications in healthcare.

They have published extensively in topics including Retinal Imaging and Analysis, Machine Learning in Healthcare, Artificial Intelligence in Healthcare, Retinal Diseases and Treatments, Topic Modeling, Biomedical Text Mining and Ontologies, and Retinal and Optic Conditions.

The scientist's recent papers include the following:

  • A deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre, 2020, Nature Biomedical Engineering
  • Artificial intelligence for teleophthalmology-based diabetic retinopathy screening in a national programme: an economic analysis modelling study, 2020, The Lancet Digital Health
  • A deep learning algorithm to detect chronic kidney disease from retinal photographs in community-based populations, 2020, The Lancet Digital Health
  • Personalizing Medication Recommendation with a Graph-Based Approach, 2021, ACM Transactions on Information Systems
  • Multi-Task Learning for Diabetic Retinopathy Grading and Lesion Segmentation, 2020, Proceedings of the AAAI Conference on Artificial Intelligence

Their frequent coauthors include Wynne Hsu, Ngiap Chuan Tan, Tien Yin Wong, Hao Sen Andrew Fang, and Dejiang Xu.

Mong Li Lee publishes regularly in venues such as arXiv (Cornell University), The Lancet Digital Health, Scientific Reports, PLoS ONE, and the Journal of the American Medical Informatics Association.

Best Publications

  • Development and Validation of a Deep Learning System for Diabetic Retinopathy and Related Eye Diseases Using Retinal Images From Multiethnic Populations With Diabetes.

    Daniel Shu Wei Ting;Daniel Shu Wei Ting;Carol Yim Lui Cheung;Carol Yim Lui Cheung;Gilbert Lim;Gavin Siew Wei Tan;Gavin Siew Wei Tan

  • Artificial intelligence using deep learning to screen for referable and vision-threatening diabetic retinopathy in Africa: a clinical validation study.

    Valentina Bellemo;Zhan W Lim;Gilbert Lim;Quang D Nguyen

  • A prime number labeling scheme for dynamic ordered XML trees

    X. Wu;M.L. Lee;W. Hsu

  • XClust: clustering XML schemas for effective integration

    Mong Li Lee;Liang Huai Yang;Wynne Hsu;Xia Yang

  • Supporting frequent updates in R-trees: a bottom-up approach

    Mong Li Lee;Wynne Hsu;Christian S. Jensen;Bin Cui

  • An effective approach to detect lesions in color retinal images

    Huan Wang;Wynne Hsu;Kheng Guan Goh;Mong Li Lee

  • Cleansing Data for Mining and Warehousing

    Mong-Li Lee;Tok Wang Ling;Hongjun Lu;Yee Teng Ko

  • Artificial intelligence for teleophthalmology-based diabetic retinopathy screening in a national programme: an economic analysis modelling study

    Yuchen Xie;Quang D Nguyen;Haslina Hamzah;Gilbert Lim

  • A deep learning algorithm to detect chronic kidney disease from retinal photographs in community-based populations

    Charumathi Sabanayagam;Dejiang Xu;Daniel Sw Ting;Simon Nusinovici

  • Image Mining: Trends and Developments

    Wynne Hsu;Mong Li Lee;Ji Zhang

  • IntelliClean: a knowledge-based intelligent data cleaner

    Mong Li Lee;Tok Wang Ling;Wai Lup Low

  • Designing Functional Dependencies for XML

    Mong-Li Lee;Tok Wang Ling;Wai Lup Low

  • Mining relationships among interval-based events for classification

    Dhaval Patel;Wynne Hsu;Mong Li Lee

  • ICICLES: Self-Tuning Samples for Approximate Query Answering

    Venkatesh Ganti;Mong-Li Lee;Raghu Ramakrishnan

  • A knowledge-based approach for duplicate elimination in data cleaning

    Wai Lup Low;Mong Li Lee;Tok Wang Ling

  • Image mining: issues, frameworks and techniques

    Ji Zhang;Wynne Hsu;Mong Li Lee

  • NeMoFinder: dissecting genome-wide protein-protein interactions with meso-scale network motifs

    Jin Chen;Wynne Hsu;Mong Li Lee;See-Kiong Ng

  • Artificial Intelligence Screening for Diabetic Retinopathy: the Real-World Emerging Application

    Valentina Bellemo;Gilbert Lim;Tyler Hyungtaek Rim;Gavin S W Tan

  • BORDER: efficient computation of boundary points

    Chenyi Xia;W. Hsu;M.L. Lee;B.C. Ooi

  • Automatic grading of retinal vessel caliber

    Huiqi Li;W. Hsu;Mong Li Lee;Tien Yin Wong

  • Efficient mining of XML query patterns for caching

    Liang Huai Yang;Mong Li Lee;Wynne Hsu

  • The role of domain knowledge in the detection of retinal hard exudates

    W. Hsu;P.M.D.S. Pallawala;Mong Li Lee;Kah-Guan Au Eong

Frequent Co-Authors

Wynne Hsu
Wynne Hsu National University of Singapore
Tok Wang Ling
Tok Wang Ling National University of Singapore
Jie Jin Wang
Jie Jin Wang University of Sydney
Beng Chin Ooi
Beng Chin Ooi National University of Singapore
Kian-Lee Tan
Kian-Lee Tan National University of Singapore
See-Kiong Ng
See-Kiong Ng National University of Singapore
Limsoon Wong
Limsoon Wong National University of Singapore
Jeffrey Xu Yu
Jeffrey Xu Yu Chinese University of Hong Kong
Sudha Ram
Sudha Ram University of Arizona
Silvana Castano
Silvana Castano University of Milan

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