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Computational and Mathematical Methods in Medicine|February 1, 2013
Two-dimensional matrix algorithm using detrended fluctuation analysis to distinguish Burkitt and diffuse large B-cell lymphomaRong-Guan Yeh, Chung-Wu Lin, Maysam F Abbod, et al.
Mathematical Biosciences and Engineering : MBE|September 14, 2021
Depth of anesthesia prediction via EEG signals using convolutional neural network and ensemble empirical mode decompositionRavichandra Madanu, Farhan Rahman, Maysam F Abbod, et al.
The Journal of Urology|August 19, 2007
Application of artificial intelligence to the management of urological cancerMaysam F Abbod, James W F Catto, Derek A Linkens, et al.
Peerj|May 31, 2018
Sample entropy analysis for the estimating depth of anaesthesia through human EEG signal at different levels of unconsciousness during surgeriesQuan Liu, Li Ma, Shou-Zen Fan, et al.
The Journal of Urology|January 13, 2006
Neuro-fuzzy modeling: an accurate and interpretable method for predicting bladder cancer progressionJames W F Catto, Maysam F Abbod, Derek A Linkens, et al.
Journal of Neural Engineering|October 25, 2021
Electroencephalogram variability analysis for monitoring depth of anesthesiaYi-Feng Chen, Shou-Zen Fan, Maysam F Abbod, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society|April 10, 2017
Quasi-Periodicities Detection Using Phase-Rectified Signal Averaging in EEG Signals as a Depth of Anesthesia MonitorQuan Liu, Yi-Feng Chen, Shou-Zen Fan, et al.
Medical & Biological Engineering & Computing|December 21, 2016
EEG artifacts reduction by multivariate empirical mode decomposition and multiscale entropy for monitoring depth of anaesthesia during surgeryQuan Liu, Yi-Feng Chen, Shou-Zen Fan, et al.
Computational and Mathematical Methods in Medicine|October 23, 2015
EEG Signals Analysis Using Multiscale Entropy for Depth of Anesthesia Monitoring during Surgery through Artificial Neural NetworksQuan Liu, Yi-Feng Chen, Shou-Zen Fan, et al.
BMC Musculoskeletal Disorders|July 17, 2013
Hip fracture risk assessment: artificial neural network outperforms conditional logistic regression in an age- and sex-matched case control studyWo-Jan Tseng, Li-Wei Hung, Jiann-Shing Shieh, et al.
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