World's Best Scientists 2026 revealed!

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Computer Science

D-Index
36
Citations
6235
World Ranking
11173
National Ranking
339

Overview

Sai Ho Ling is affiliated with the University of Technology Sydney in Australia. Their research spans the intersection of medicine, engineering, and computer science, with a substantial focus on biomedical engineering and artificial intelligence applied to medical imaging and analysis.

The scientist's work primarily concentrates on several specific topics:

  • Medical Imaging and Analysis
  • Medical Image Segmentation Techniques
  • AI in cancer detection
  • Lung Cancer Diagnosis and Treatment
  • EEG and Brain-Computer Interfaces
  • Radiomics and Machine Learning in Medical Imaging
  • Scoliosis diagnosis and treatment

The main fields of study they contribute to include:

  • Medicine
  • Engineering
  • Computer Science

Subfields within their research are centered on:

  • Biomedical Engineering
  • Artificial Intelligence
  • Cognitive Neuroscience
  • Radiology, Nuclear Medicine and Imaging
  • Computer Vision and Pattern Recognition

Sai Ho Ling has coauthored frequently with several researchers, including:

  • Steven W. Su
  • Juan Lyu
  • Yong-Ping Zheng
  • Zixun Huang
  • Afshin Shoeibi

Their research has been published extensively in a range of academic venues. The most frequent publication outlets include:

  • Sensors
  • arXiv (Cornell University)
  • Biomedical Signal Processing and Control
  • SSRN Electronic Journal
  • Computerized Medical Imaging and Graphics

Some recent notable papers by Sai Ho Ling are:

  • VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images, 2021, Medical Image Analysis
  • Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review, 2022, Frontiers in Molecular Neuroscience
  • Convolutional Neural Networks-Based Lung Nodule Classification: A Surrogate-Assisted Evolutionary Algorithm for Hyperparameter Optimization, 2021, IEEE Transactions on Evolutionary Computation
  • Diagnosis of brain diseases in fusion of neuroimaging modalities using deep learning: A review, 2022, Information Fusion
  • Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review, 2023, Computers in Biology and Medicine

Best Publications

  • Tuning of the structure and parameters of a neural network using an improved genetic algorithm

    F.H.F. Leung;H.K. Lam;S.H. Ling;P.K.S. Tam

  • Hybrid Particle Swarm Optimization With Wavelet Mutation and Its Industrial Applications

    S.H. Ling;H.H.C. Iu;K.Y. Chan;H.K. Lam

  • VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images

    Anjany Sekuboyina;Malek E. Husseini;Amirhossein Bayat;Maximilian Löffler

  • Driver Fatigue Classification With Independent Component by Entropy Rate Bound Minimization Analysis in an EEG-Based System

    Rifai Chai;Ganesh R. Naik;Tuan Nghia Nguyen;Sai Ho Ling

  • Improved Hybrid Particle Swarm Optimized Wavelet Neural Network for Modeling the Development of Fluid Dispensing for Electronic Packaging

    S.H. Ling;H. Iu;F.H.F. Leung;K.Y. Chan

  • A novel genetic-algorithm-based neural network for short-term load forecasting

    S.H. Ling;F.H.F. Leung;H.K. Lam;Yim-Shu Lee

  • Improving EEG-Based Driver Fatigue Classification Using Sparse-Deep Belief Networks.

    Rifai Chai;Sai Ho Ling;Phyo Phyo San;Ganesh R. Naik

  • Short-term electric load forecasting based on a neural fuzzy network

    S.H. Ling;F.H.F. Leung;H.K. Lam;P.K.S. Tam

  • An Improved Genetic Algorithm with Average-bound Crossover and Wavelet Mutation Operations

    S. H. Ling;F. H. F. Leung

  • Review on Electrical Impedance Tomography: Artificial Intelligence Methods and its Applications

    Talha Ali Khan;Sai Ho Ling

  • Brain–Computer Interface Classifier for Wheelchair Commands Using Neural Network With Fuzzy Particle Swarm Optimization

    Rifai Chai;Sai Ho Ling;Gregory P. Hunter;Yvonne Tran

  • Integrated computational intelligent paradigm for nonlinear electric circuit models using neural networks, genetic algorithms and sequential quadratic programming

    Ammara Mehmood;Aneela Zameer;Sai Ho Ling;Ata ur Rehman

  • Efficient diagnosis system for Parkinson's disease using deep belief network

    Ali H. Al-Fatlawi;Mohammed H. Jabardi;Sai Ho Ling

  • Design of neuro-computing paradigms for nonlinear nanofluidic systems of MHD Jeffery–Hamel flow

    Ammara Mehmood;Nouman-ul Haq;Aneela Zameer;Sai Ho Ling

  • Diagnosis of hypoglycemic episodes using a neural network based rule discovery system

    K. Y. Chan;S. H. Ling;T. S. Dillon;H. T. Nguyen

  • Tuning of the structure and parameters of neural network using an improved genetic algorithm

    H.K. Lam;S.H. Ling;F.H.F. Leung;P.K.S. Tam

  • Improved genetic algorithm for economic load dispatch with valve-point loadings

    S.H. Ling;H.K. Lam;F.H.F. Leung;Y.S. Lee

  • A study of neural-network-based classifiers for material classification

    H. K. Lam;Udeme Ekong;Hongbin Liu;Bo Xiao

  • Synchronization of Chaotic Systems Using Time-Delayed Fuzzy State-Feedback Controller

    H.K. Lam;Wing-Kuen Ling;H.H.-C. Lu;S.S.H. Ling

  • A novel hybrid gravitational search particle swarm optimization algorithm

    Talha Ali Khan;Sai Ho Ling

  • Optimal and stable fuzzy controllers for nonlinear systems based on an improved genetic algorithm

    F.H.F. Leung;H.K. Lam;S.H. Ling;P.K.S. Tam

Frequent Co-Authors

Frank H. F. Leung
Frank H. F. Leung Hong Kong Polytechnic University
Hak-Keung Lam
Hak-Keung Lam King's College London
Kit Yan Chan
Kit Yan Chan Curtin University
Herbert Ho-Ching Iu
Herbert Ho-Ching Iu University of Western Australia
Tharam S. Dillon
Tharam S. Dillon La Trobe University
Yong-Ping Zheng
Yong-Ping Zheng Hong Kong Polytechnic University
Ganesh R. Naik
Ganesh R. Naik Flinders University
Ashley Craig
Ashley Craig University of Sydney
Hongbin Liu
Hongbin Liu King's College London
Muhammad Asif Zahoor Raja
Muhammad Asif Zahoor Raja National Yunlin University of Science and Technology

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