World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
6773
World Ranking
8875
National Ranking
6

Overview

Keun Ho Ryu is affiliated with Chungbuk National University in South Korea. Their research spans multiple fields, primarily situated at the intersection of computer science, biochemistry, genetics and molecular biology, and medicine.

The main fields of study in their work include:

  • Computer Science
  • Biochemistry, Genetics and Molecular Biology
  • Medicine

They have also contributed extensively to several subfields, such as:

  • Artificial Intelligence
  • Molecular Biology
  • Health Information Management
  • Computer Vision and Pattern Recognition
  • Management Science and Operations Research

Keun Ho Ryu's research focuses on a range of topics, including:

  • Artificial Intelligence in Healthcare
  • Topic Modeling
  • Biomedical Text Mining and Ontologies
  • Machine Learning in Healthcare
  • Imbalanced Data Classification Techniques
  • Traditional Chinese Medicine Studies
  • Time Series Analysis and Forecasting

The scientist has established collaboration with several frequent co-authors identified as:

  • Van-Huy Pham
  • Nipon Theera-Umpon
  • Lkhagvadorj Munkhdalai
  • Khishigsuren Davagdorj
  • Tsatsral Amarbayasgalan

Their publications have appeared regularly in several venues, particularly:

  • IEEE Access
  • International Journal of Environmental Research and Public Health
  • Applied Sciences
  • Sensors
  • Computational and Mathematical Methods in Medicine

Selected recent papers include:

  • XGBoost-Based Framework for Smoking-Induced Noncommunicable Disease Prediction, 2020, International Journal of Environmental Research and Public Health
  • An Efficient Prediction Method for Coronary Heart Disease Risk Based on Two Deep Neural Networks Trained on Well-Ordered Training Datasets, 2021, IEEE Access
  • Unsupervised Anomaly Detection Approach for Time-Series in Multi-Domains Using Deep Reconstruction Error, 2020, Symmetry
  • Explainable Artificial Intelligence Based Framework for Non-Communicable Diseases Prediction, 2021, IEEE Access
  • A Comparative Analysis of Machine Learning Methods for Class Imbalance in a Smoking Cessation Intervention, 2020, Applied Sciences

In addition to journal publications, Keun Ho Ryu has authored a book published by Springer Nature titled Advances in Intelligent Information Hiding and Multimedia Signal Processing (2021).

Best Publications

  • The CHEMDNER corpus of chemicals and drugs and its annotation principles.

    Martin Krallinger;Obdulia Rabal;Florian Leitner;Miguel Vazquez

  • Landslide susceptibility mapping in Injae, Korea, using a decision tree

    Young-Kwang Yeon;Jong-Gyu Han;Keun Ho Ryu

  • Mining association rules on significant rare data using relative support

    Hyunyoon Yun;Danshim Ha;Buhyun Hwang;Keun Ho Ryu

  • Semantic-Emotion Neural Network for Emotion Recognition From Text

    Erdenebileg Batbaatar;Meijing Li;Keun Ho Ryu

  • Comparing the normalization methods for the differential analysis of Illumina high-throughput RNA-Seq data.

    Peipei Li;Yongjun Piao;Ho Sun Shon;Keun Ho Ryu

  • High utility itemset mining with techniques for reducing overestimated utilities and pruning candidates

    Unil Yun;Heungmo Ryang;Keun Ho Ryu

  • An Empirical Comparison of Machine-Learning Methods on Bank Client Credit Assessments

    Lkhagvadorj Munkhdalai;Tsendsuren Munkhdalai;Oyun-Erdene Namsrai;Jong Yun Lee

  • Mining biosignal data: coronary artery disease diagnosis using linear and nonlinear features of HRV

    Heon Gyu Lee;Ki Yong Noh;Keun Ho Ryu

  • HOXA9, ISL1 and ALDH1A3 methylation patterns as prognostic markers for nonmuscle invasive bladder cancer: Array‐based DNA methylation and expression profiling

    Yong June Kim;Hyung Yoon Yoon;Ji Sang Kim;Ho Won Kang

  • Sliding window based weighted maximal frequent pattern mining over data streams

    Gangin Lee;Unil Yun;Keun Ho Ryu

  • Unsupervised Novelty Detection Using Deep Autoencoders with Density Based Clustering

    Tsatsral Amarbayasgalan;Bilguun Jargalsaikhan;Keun Ho Ryu

  • Air Pollution Monitoring System based on Geosensor Network

    Young Jin Jung;Yang Koo Lee;Dong Gyu Lee;Keun Ho Ryu

  • Efficient frequent pattern mining based on Linear Prefix tree

    Gwangbum Pyun;Unil Yun;Keun Ho Ryu

  • A Novel DBSCAN-Based Defect Pattern Detection and Classification Framework for Wafer Bin Map

    Cheng Hao Jin;Hyuk Jun Na;Minghao Piao;Gouchol Pok

  • An ensemble correlation-based gene selection algorithm for cancer classification with gene expression data

    Yongjun Piao;Minghao Piao;Kiejung Park;Keun Ho Ryu

  • Mining maximal frequent patterns by considering weight conditions over data streams

    Unil Yun;Gangin Lee;Keun Ho Ryu

  • XGBoost-Based Framework for Smoking-Induced Noncommunicable Disease Prediction.

    Khishigsuren Davagdorj;Van Huy Pham;Nipon Theera-Umpon;Keun Ho Ryu;Keun Ho Ryu

  • Mixture of Activation Functions With Extended Min-Max Normalization for Forex Market Prediction

    Lkhagvadorj Munkhdalai;Tsendsuren Munkhdalai;Kwang Ho Park;Heon Gyu Lee

  • A method for predicting future location of mobile user for location-based services system

    Thi Hong Nhan Vu;Keun Ho Ryu;Namkyu Park

  • A Data Mining Approach for Coronary Heart Disease Prediction using HRV Features and Carotid Arterial Wall Thickness

    Heon Gyu Lee;Ki Yong Noh;Keun Ho Ryu

  • Temporal moving pattern mining for location-based service

    Jun Wook Lee;Ok Hyun Paek;Keun Ho Ryu

  • Subspace Projection Method Based Clustering Analysis in Load Profiling

    Minghao Piao;Ho Sun Shon;Jong Yun Lee;Keun Ho Ryu

Frequent Co-Authors

Unil Yun
Unil Yun Sejong University
Wun-Jae Kim
Wun-Jae Kim Chungbuk National University
Jaewoo Kang
Jaewoo Kang Korea University
David Gilbert
David Gilbert Brunel University London
Dongwon Lee
Dongwon Lee Pennsylvania State University
Tae-Wook Kim
Tae-Wook Kim Jeonbuk National University
Huidong Shi
Huidong Shi Augusta University
Rong Xiang
Rong Xiang Nankai University
Tim Rocktäschel
Tim Rocktäschel University College London

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