Items where Author is "Acharya, U.R."

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Article

Acharya, U.R. and Fujita, H. and Oh, S.L. and Hagiwara, Y. and Tan, J.H. and Adam, M. (2017) Application of deep convolutional neural network for automated detection of myocardial infarction using ECG signals. Information Sciences, 415. pp. 190-198. ISSN 0020-0255, DOI https://doi.org/10.1016/j.ins.2017.06.027.

Kumar, M. and Pachori, R.B. and Acharya, U.R. (2017) Automated Diagnosis of Myocardial Infarction ECG Signals Using Sample Entropy in Flexible Analytic Wavelet Transform Framework. Entropy, 19 (9). p. 488. ISSN 1099-4300, DOI https://doi.org/10.3390/e19090488.

Acharya, U.R. and Fujita, H. and Sudarshan, V.K. and Oh, S.L. and Adam, M. and Tan, J.H. and Koo, J.H. and Jain, A. and Lim, C.M. and Chua, K.C. (2017) Automated characterization of coronary artery disease, myocardial infarction, and congestive heart failure using contourlet and shearlet transforms of electrocardiogram signal. Knowledge-Based Systems, 132. pp. 156-166. ISSN 0950-7051, DOI https://doi.org/10.1016/j.knosys.2017.06.026.

Acharya, U.R. and Fujita, H. and Lih, O.S. and Adam, M. and Tan, J.H. and Chua, C.K. (2017) Automated detection of coronary artery disease using different durations of ECG segments with convolutional neural network. Knowledge-Based Systems, 132. pp. 62-71. ISSN 0950-7051, DOI https://doi.org/10.1016/j.knosys.2017.06.003.

Bhattacharyya, A. and Pachori, R.B. and Upadhyay, A. and Acharya, U.R. (2017) Tunable-Q Wavelet Transform Based Multiscale Entropy Measure for Automated Classification of Epileptic EEG Signals. Applied Sciences, 7 (4). p. 385. ISSN 2076-3417, DOI https://doi.org/10.3390/app7040385.

Bhattacharyya, A. and Pachori, R.B. and Acharya, U.R. (2017) Tunable-Q Wavelet Transform Based Multivariate Sub-Band Fuzzy Entropy with Application to Focal EEG Signal Analysis. Entropy, 19 (3). p. 99. ISSN 1099-4300, DOI https://doi.org/10.3390/e19030099.

Kumar, M. and Pachori, R.B. and Acharya, U.R. (2017) Use of Accumulated Entropies for Automated Detection of Congestive Heart Failure in Flexible Analytic Wavelet Transform Framework Based on Short-Term HRV Signals. Entropy, 19 (3). p. 92. ISSN 1099-4300, DOI https://doi.org/10.3390/e19030092.

Acharya, U.R. and Raghavendra, U. and Fujita, H. and Hagiwara, Y. and Koh, J.E.W. and Jen Hong, T. and Sudarshan, V.K. and Vijayananthan, A. and Yeong, C.H. and Gudigar, A. and Ng, K.H. (2016) Automated characterization of fatty liver disease and cirrhosis using curvelet transform and entropy features extracted from ultrasound images. Computers in Biology and Medicine, 79. pp. 250-258. ISSN 0010-4825, DOI https://doi.org/10.1016/j.compbiomed.2016.10.022.

Acharya, U.R. and Fujita, H. and Sudarshan, V.K. and Oh, S.L. and Adam, M. and Koh, J.E.W. and Tan, J.H. and Ghista, D.N. and Martis, R.J. and Chua, C.K. and Poo, C.K. and Tan, R.S. (2016) Automated detection and localization of myocardial infarction using electrocardiogram: a comparative study of different leads. Knowledge-Based Systems, 99. pp. 146-156. ISSN 0950-7051, DOI https://doi.org/10.1016/j.knosys.2016.01.040.

Acharya, U.R. and Fujita, H. and Bhat, S. and Koh, J.E.W. and Adam, M. and Ghista, D.N. and Sudarshan, V.K. and Chua, K.P. and Chua, K.C. and Molinari, F. and Ng, E.Y.K. and Tan, R.S. (2016) Automated diagnosis of diabetes using entropies and diabetic index. Journal of Mechanics in Medicine and Biology (jmmb), 16 (01). p. 1640008. ISSN 0219-5194, DOI https://doi.org/10.1142/S021951941640008X.

Acharya, U.R. and Mookiah, M.R.K. and Koh, J.E.W. and Tan, J.H. and Bhandary, S.V. and Rao, A.K. and Fujita, H. and Hagiwara, Y. and Chua, C.K. and Laude, A. (2016) Automated screening system for retinal health using bi-dimensional empirical mode decomposition and integrated index. Computers in Biology and Medicine, 75. pp. 54-62. ISSN 0010-4825, DOI https://doi.org/10.1016/j.compbiomed.2016.04.015.

Acharya, U.R. and Fujita, H. and Bhat, S. and Raghavendra, U. and Gudigar, A. and Molinari, F. and Vijayananthan, A. and Ng, K.H. (2016) Decision support system for fatty liver disease using GIST descriptors extracted from ultrasound images. Information Fusion, 29. pp. 32-39. ISSN 1566-2535, DOI https://doi.org/10.1016/j.inffus.2015.09.006.

Acharya, U.R. and Mookiah, M.R.K. and Koh, J.E.W. and Tan, J.H. and Noronha, K. and Bhandary, S.V. and Rao, A.K. and Hagiwara, Y. and Chua, C.K. and Laude, A. (2016) Novel risk index for the identification of age-related macular degeneration using radon transform and DWT features. Computers in Biology and Medicine, 73. pp. 131-140. ISSN 0010-4825, DOI https://doi.org/10.1016/j.compbiomed.2016.04.009.

Acharya, U.R. and Chowriappa, P. and Fujita, H. and Bhat, S. and Dua, S. and Koh, J.E.W. and Eugene, L.W.J. and Kongmebhol, P. and Ng, K.H. (2016) Thyroid lesion classification in 242 patient population using Gabor transform features from high resolution ultrasound images. Knowledge-Based Systems, 107. pp. 235-245. ISSN 0950-7051, DOI https://doi.org/10.1016/j.knosys.2016.06.010.

Acharya, U.R. and Fujita, H. and Sudarshan, V.K. and Mookiah, M.R.K. and Koh, J.E.W. and Tan, J.H. and Hagiwara, Y. and Chua, C.K. and Junnarkar, S.P. and Vijayananthan, A. and Ng, K.H. (2016) An integrated index for identification of fatty liver disease using radon transform and discrete cosine transform features in ultrasound images. Information Fusion, 31. pp. 43-53. ISSN 1566-2535, DOI https://doi.org/10.1016/j.inffus.2015.12.007.

Acharya, U.R. and Sudarshan, V.K. and Adeli, H. and Santhosh, J. and Koh, J.E.W. and Puthankatti, S.D. and Adeli, A. (2016) A novel depression diagnosis index using nonlinear features in EEG signals. European Neurology, 74 (1-2). pp. 79-83. ISSN 0014-3022, DOI https://doi.org/10.1159/000438457.

Acharya, U.R. and Sudarshan, V.K. and Ghista, D.N. and Lim, W.J.E. and Molinari, F. and Sankaranarayanan, M. (2015) Computer-aided diagnosis of diabetic subjects by heart rate variability signals using discrete wavelet transform method. Knowledge-Based Systems, 81. pp. 56-64. DOI https://doi.org/10.1016/j.knosys.2015.02.005.

Acharya, U.R. and Molinari, F. and Sree, S.V. and Swapna, G. and Saba, L. and Guerriero, S. and Suri, J.S. (2015) Ovarian tissue characterization in ultrasound: A Review. Technology in Cancer Research & Treatment, 14 (3). pp. 251-261. ISSN 1533-0338, DOI https://doi.org/10.1177/1533034614547445.

Acharya, U.R. and Sree, S.V. and Molinari, F. and Saba, L. and Nicolaides, A. and Suri, J.S. (2015) An automated technique for carotid far wall classification using grayscale features and wall thickness variability. Journal of Clinical Ultrasound, 43 (5). pp. 302-311. ISSN 0091-2751, DOI https://doi.org/10.1002/jcu.22183.

Acharya, U.R. and Faust, O. and Molinari, F. and Sree, S.V. and Junnarkar, S.P. and Sudarshan, V. (2015) Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm. Knowledge-Based Systems, 75. pp. 66-77. ISSN 0950-7051, DOI https://doi.org/10.1016/j.knosys.2014.11.021.

Acharya, U.R. and Ng, E.Y.K. and Eugene, L.W.J. and Noronha, K.P. and Min, L.C. and Nayak, K.P. and Bhandary, S.V. (2015) Decision support system for the glaucoma using Gabor transformation. Biomedical Signal Processing and Control, 15. pp. 18-26. ISSN 1746-8094,

Mookiah, M.R.K. and Acharya, U.R. and Chandran, V. and Martis, R.J. and Tan, J.H. and Koh, J.E.W. and Chua, C.K. and Tong, L. and Laude, A. (2015) Application of higher-order spectra for automated grading of diabetic maculopathy. Medical & Biological Engineering & Computing, 53 (12, SI). pp. 1319-1331. ISSN 0140-0118,

Vidya, K.S. and Ng, E.Y.K. and Acharya, U.R. and Chou, S.M. and Tan, R.S. and Ghista, D.N. (2015) Computer-aided diagnosis of Myocardial Infarction using ultrasound images with DWT, GLCM and HOS methods: A comparative study. Computers in Biology and Medicine, 62. pp. 86-93. ISSN 0010-4825, DOI https://doi.org/10.1016/j.compbiomed.2015.03.033.

Acharya, U.R. and Sudarshan, V.K. and Adeli, H. and Santhosh, J. and Koh, J.E.W. and Adeli, A. (2015) Computer-aided diagnosis of depression using EEG signals. European Neurology, 73 (5-6). pp. 329-336. ISSN 0014-3022 , DOI https://doi.org/10.1159/000381950.

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