His primary scientific interests are in Thermography, Artificial intelligence, Breast cancer, Pattern recognition and Biomedical engineering. His studies deal with areas such as Image segmentation, Surgery, Breast thermography, Mammography and Early detection as well as Thermography. Much of his study explores Artificial intelligence relationship to Computer vision.
His Breast cancer study combines topics in areas such as Image processing, Texture, Artificial neural network and Discrete wavelet transform. His Pattern recognition study incorporates themes from Cross-validation, Ictal, Electroencephalography, Decision tree learning and Signal processing. His Biomedical engineering research is multidisciplinary, incorporating elements of Ocular surface, 3D reconstruction, Optics, 3D printing and Coronary arteries.
Eddie Y. K. Ng mainly investigates Artificial intelligence, Mechanics, Thermography, Pattern recognition and Internal medicine. His Artificial intelligence research integrates issues from Breast cancer and Computer vision. The concepts of his Breast cancer study are interwoven with issues in Image processing and Medical physics.
Many of his studies on Mechanics involve topics that are commonly interrelated, such as Gas compressor. Eddie Y. K. Ng has included themes like Mammography and Biomedical engineering in his Thermography study. Eddie Y. K. Ng has researched Heat transfer in several fields, including Mechanical engineering and Microchannel.
Artificial intelligence, Special section, Pattern recognition, Thermography and Stenosis are his primary areas of study. In the subject of general Artificial intelligence, his work in Segmentation is often linked to Estimation, thereby combining diverse domains of study. His Pattern recognition research is multidisciplinary, incorporating perspectives in Ambulatory blood pressure, Masked Hypertension and Blood pressure.
In most of his Thermography studies, his work intersects topics such as Biomedical engineering. In his study, Image contrast, Iterative reconstruction, Infrared and Pixel is inextricably linked to High contrast, which falls within the broad field of Biomedical engineering. The various areas that Eddie Y. K. Ng examines in his Stenosis study include Thermal lag, Blood flow, Carotid arteries, Ultrasound and Stroke.
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Thermography, Stenosis and Biomedical engineering. His biological study spans a wide range of topics, including Spatial frequency and Pulse. His Pattern recognition research is multidisciplinary, relying on both Image resolution, QRS complex, Shuffled frog leaping algorithm and Heart rate.
In his study, Segmentation is strongly linked to Image, which falls under the umbrella field of Thermography. His research in Stenosis intersects with topics in Stroke, Hemodynamics, Diastole and Ultrasound. His research investigates the connection with Biomedical engineering and areas like Vascular Stenosis which intersect with concerns in Optical coherence tomography.
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Automated diagnosis of arrhythmia using combination of CNN and LSTM techniques with variable length heart beats
Shu Lih Oh;Eddie Yin Kwee Ng;Ru San Tan;U. Rajendra Acharya.
Computers in Biology and Medicine (2018)
Application of empirical mode decomposition (emd) for automated detection of epilepsy using EEG signals.
Roshan Joy Martis;U. Rajendra Acharya;U. Rajendra Acharya;Jen Hong Tan;Andrea Petznick.
International Journal of Neural Systems (2012)
Analysis of IR thermal imager for mass blind fever screening.
Eddie Y K Ng;G J L Kaw;W M Chang.
Microvascular Research (2004)
Application of Higher Order Spectra for the Identification of Diabetes Retinopathy Stages
Rajendra Acharya U;Chua Kuang Chua;E. Y. Ng;Wenwei Yu.
Journal of Medical Systems (2008)
Statistical analysis of healthy and malignant breast thermography.
E. Y. K. Ng;L. N. Ung;F. C. Ng;L. S. J. Sim.
Journal of Medical Engineering & Technology (2001)
Breast imaging: A survey
Subbhuraam Vinitha Sree;Eddie Yin-Kwee Ng;Rajendra U Acharya;Oliver Faust.
World journal of clinical oncology (2011)
A novel cognitive interpretation of breast cancer thermography with complementary learning fuzzy neural memory structure
T. Z. Tan;C. Quek;G. S. Ng;E. Y. K. Ng.
Expert Systems With Applications (2007)
Application of K- and Fuzzy c-Means for Color Segmentation of Thermal Infrared Breast Images
M. Etehadtavakol;S. Sadri;E. Y. Ng.
Journal of Medical Systems (2010)
Computer simulation in conjunction with medical thermography as an adjunct tool for early detection of breast cancer.
Eddie Y-K Ng;NM Sudharsan.
BMC Cancer (2004)
Breast cancer detection from thermal images using bispectral invariant features
Mahnaz EtehadTavakol;Vinod Chandran;E.Y.K. Ng;Raheleh Kafieh.
International Journal of Thermal Sciences (2013)
Journal of Medical Imaging and Health Informatics
(Impact Factor: 0.659)
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