References
- Acharya RU, Faust O, Alvin AP, Sree SV, Molinari F, Saba L, Nicolaides A, Suri JS. 2012. Symptomatic vs. asymptomatic plaque classification in carotid ultrasound. J Med Syst. 36(3):1861–1871. doi:https://doi.org/10.1007/s10916-010-9645-2.
- Acharya UR, Mookiah MR, Sree SV, Afonso D, Sanches J, Shafique S, Nicolaides A, Pedro LM, E Fernandes JF, Suri JS. 2013. Atherosclerotic plaque tissue characterization in 2D ultrasound longitudinal carotid scans for automated classification: a paradigm for stroke risk assessment. Med Biol Eng Comput. 51(5):513–523. doi:https://doi.org/10.1007/s11517-012-1019-0.
- Acharya UR, Sree SV, Ribeiro R, Krishnamurthi G, Marinho RT, Sanches J, Suri JS. 2012. Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm. Med Phys. 39(7Part1):4255–4264. doi:https://doi.org/10.1118/1.4725759.
- Afonso D, Seabra J, Pedro LM, E Fernandes JF, Sanches JM. 2015. An ultrasonographic risk score for detecting symptomatic carotid atherosclerotic plaques. IEEE J Biomed Health Inf. 19(4):1505–1513. doi:https://doi.org/10.1109/JBHI.2014.2359236.
- Amoedo J, Ramió-Pujol S, Bahí A, Oliver L, Puig-Amiel C, Gilabert P, Clos A, Mañosa M, Cañete F, Serra-Pagès M, et al. 2018. Su1828-raid-CD monitor: a new non-invasive method to determine endoscopic activity in patients with inflammatory bowel diseases. Gastroenterology. 154(6):S–599. doi:https://doi.org/10.1016/S0016-5085(18)32174-7.
- Arias Lorza AM, Van Engelen A, Petersen J, Van Der Lugt A, De Bruijne M. 2018. Maximization of regional probabilities using optimal surface graphs: application to carotid artery segmentation in MRI. Med Phys. 45(3):1159–1169. doi:https://doi.org/10.1002/mp.12771.
- Beritelli F, Capizzi G, Sciuto GL, Napoli C, Scaglione F. 2018. Automatic heart activity diagnosis based on Gram polynomials and probabilistic neural networks. Biomed Eng Lett. 8(1):77–85. doi:https://doi.org/10.1007/s13534-017-0046-z.
- Bonanno L, Sottile F, Ciurleo R, Di Lorenzo G, Bruschetta D, Bramanti A, Ascenti G, Bramanti P, Marino S. 2017. Automatic algorithm for segmentation of atherosclerotic carotid plaque. J Stroke Cerebrovascular Dis. 26(2):411–416. doi:https://doi.org/10.1016/j.jstrokecerebrovasdis.2016.09.045.
- Cheng J, Chen Y, Yu Y, Chiu B. 2018. Carotid plaque segmentation from three-dimensional ultrasound images by direct three-dimensional sparse field level-set optimization. Comput Biol Med. 94:27–40. doi:https://doi.org/10.1016/j.compbiomed.2018.01.002.
- Christodoulou CI, Pattichis CS, Pantziaris M, Nicolaides A. 2003. Texture-based classification of atherosclerotic carotid plaques. IEEE Trans Med Imaging. 22(7):902–912. doi:https://doi.org/10.1109/TMI.2003.815066.
- Elder AM, Ng MK. 2017. Iodide mumps complicating coronary and carotid angiography. Heart Lung Circ. 26(2):e14–5. doi:https://doi.org/10.1016/j.hlc.2016.05.126.
- Geroulakos G, Domjan J, Nicolaides A, Stevens J, Labropoulos N, Ramaswami G, Belcaro G, Mansfield A. 1994. Ultrasonic carotid artery plaque structure and the risk of cerebral infarction on computed tomography. J Vasc Surg. 20(2):263–266. doi:https://doi.org/10.1016/0741-5214(94)90014-0.
- Hart RG, Diener HC, Coutts SB, Easton JD, Granger CB, O’Donnell MJ, Sacco RL, Connolly SJ. 2014. Cryptogenic stroke/ESUS international working group. Embolic strokes of undetermined source: the case for a new clinical construct. Lancet Neurol. 13(4):429–438. doi:https://doi.org/10.1016/S1474-4422(13)70310-7.
- Hassan MK, El Desouky AI, Elghamrawy SM, Sarhan AM. 2019. A hybrid real-time remote monitoring framework with NB-WOA algorithm for patients with chronic diseases. Future Gener Comput Syst. 93:77–95. doi:https://doi.org/10.1016/j.future.2018.10.021.
- Huang C, He Q, Huang M, Huang L, Zhao X, Yuan C, Luo J. 2017. Non-invasive identification of vulnerable atherosclerotic plaques using texture analysis in ultrasound carotid elastography: an in vivo feasibility study validated by magnetic resonance imaging. Ultrasound Med Biol. 43(4):817–830. doi:https://doi.org/10.1016/j.ultrasmedbio.2016.12.003.
- Hwang YN, Lee JH, Kim GY, Shin ES, Kim SM. 2018. Characterization of coronary plaque regions in intravascular ultrasound images using a hybrid ensemble classifier. Comput Methods Programs Biomed. 153:83–92. doi:https://doi.org/10.1016/j.cmpb.2017.10.009.
- Iannuzzi A, Wilcosky T, Mercuri M, Rubba P, Bryan FA, Bond MG. 1995. Ultrasonographic correlates of carotid atherosclerosis in transient ischemic attack and stroke. Stroke. 26(4):614–619. doi:https://doi.org/10.1161/01.STR.26.4.614.
- Johnson JL, Merrilees M, Shragge J, van Wijk K. 2018. All-optical extravascular laser-ultrasound and photoacoustic imaging of calcified atherosclerotic plaque in excised carotid artery. Photoacoustics. 9:62–72. doi:https://doi.org/10.1016/j.pacs.2018.01.002.
- Kamali R, Kheirandish S, Paktinat K. 2019. Investigation of different activities on the hemodynamic parameters of left external carotid artery using fluid–structure interaction. Iran J Sci Technol Trans Mech Eng. 43(1):91–106. doi:https://doi.org/10.1007/s40997-018-0142-4.
- Kora P, Abraham A, Meenakshi K. 2020. Heart disease detection using hybrid of bacterial foraging and particle swarm optimization. Evolving Syst. 11(1):15–28. doi:https://doi.org/10.1007/s12530-019-09312-6.
- Libby P, Theroux P. 2005. Pathophysiology of coronary artery disease. Circulation. 111(25):3481–3488. doi:https://doi.org/10.1161/CIRCULATIONAHA.105.537878.
- Mirjalili S, Gandomi AH, Mirjalili SZ, Saremi S, Faris H, Mirjalili SM. 2017. Salp Swarm Algorithm: a bio-inspired optimizer for engineering design problems. Adv Eng Softw. 114:163–191. doi:https://doi.org/10.1016/j.advengsoft.2017.07.002.
- Mythili S, Thiyagarajah K, Rajesh P, Shajin FH. 2020. Ideal position and size selection of Unified Power Flow Controllers (UPFCs) to upgrade the dynamic stability of systems: an antlion optimiser and invasive weed optimisation algorithm. HKIE Trans. 2020(27):25–37.
- Olgac U, Knight J, Poulikakos D, Saur SC, Alkadhi H, Desbiolles LM, Cattin PC, Kurtcuoglu V. 2011. Computed high concentrations of low-density lipoprotein correlate with plaque locations in human coronary arteries. J Biomech. 44(13):2466–2471. doi:https://doi.org/10.1016/j.jbiomech.2011.06.022.
- Pławiak P, Acharya UR. 2020. Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals. Neural Comput Appl. 32(15):11137–11161. doi:https://doi.org/10.1007/s00521-018-03980-2.
- Qian C, Yang X. 2018. An integrated method for atherosclerotic carotid plaque segmentation in ultrasound image. Comput Methods Programs Biomed. 153:19–32. doi:https://doi.org/10.1016/j.cmpb.2017.10.002.
- Raghavendra U, Fujita H, Gudigar A, Shetty R, Nayak K, Pai U, Samanth J, Acharya UR. 2018. Automated technique for coronary artery disease characterization and classification using DD-DTDWT in ultrasound images. Biomed Signal Process Control. 40:324–334. doi:https://doi.org/10.1016/j.bspc.2017.09.030.
- Rajesh P, Shajin FH. 2020. A multi-objective hybrid algorithm for planning electrical distribution system. International Information and Engineering Technology Association.
- Rezaei Z, Selamat A, Taki A, Rahim MS, Kadir MR. 2017. Automatic plaque segmentation based on hybrid fuzzy clustering and k nearest neighborhood using virtual histology intravascular ultrasound images. Appl Soft Comput. 53:380–395. doi:https://doi.org/10.1016/j.asoc.2016.12.048.
- Rosamond W, Flagel K, Furie K, Go A, Greenlund K, Haase N, Hailpern SM, Ho M, Howard V, Kissela B, et al. 2008. Heart disease and stroke statistics-2008 update: a report from the American Heart Association statistics committee and stroke statistics. Circulation. 117(4):e25–146. doi:https://doi.org/10.1161/CIRCULATIONAHA.107.187998
- Rothwell PM, Eliasziw M, Gutnikov SA, Fox AJ, Taylor DW, Mayberg MR, Warlow CP, Barnett HJ. 2003. Carotid endarterectomy trialists’ collaboration. Analysis of pooled data from the randomised controlled trials of endarterectomy for symptomatic carotid stenosis. Lancet. 361(9352):107–116. doi:https://doi.org/10.1016/S0140-6736(03)12228-3.
- Sakamoto A, Torii S, Jinnouchi H, Finn AV, Virmani R, Kolodgie FD. 2018. Pathologic intimal thickening: are we any closer to understand early transitional plaques that lead to symptomatic disease? Atherosclerosis. 274:227–229. doi:https://doi.org/10.1016/j.atherosclerosis.2018.04.033.
- Sánchez AVD. 2003. Advanced support vector machines and kernel methods. Neurocomputing. 55(1–2):5–20. doi:https://doi.org/10.1016/S0925-2312(03)00373-4.
- Selesnick IW, Baraniuk RG, Kingsbury NC. 2005. The dual-tree complex wavelet transform. IEEE Signal Process Mag. 22(6):123–151. doi:https://doi.org/10.1109/MSP.2005.1550194.
- Selesnick IW, Bayram İ 2009. Oscillatory plus transient signal decomposition using overcomplete rational-dilation wavelet transforms. InWavelets XIII.
- Transpire Online, 2019. A novel numerical optimization algorithm inspired from particles: particle swarm optimization, Transpire Online 2019. Available at: https://transpireonline.blog/2019/07/03/a-novel-numerical-optimization-algorithm-inspired-from-particles-particle-swarm-optimization/. [Accessed on: Sep, 2019]
- Venkataramanaiah B, Kamala J. 2020. ECG signal processing and KNN classifier-based abnormality detection by VH-doctor for remote cardiac healthcare monitoring. Soft Comput. 24(22):17457–17466. doi:https://doi.org/10.1007/s00500-020-05191-1.
- Venkatesan C, Karthigaikumar P, Paul A, Satheeskumaran S, Kumar R. 2018. ECG signal preprocessing and SVM classifier-based abnormality detection in remote healthcare applications. IEEE Access. 6:9767–9773. doi:https://doi.org/10.1109/ACCESS.2018.2794346.
- Vijayashree J, Sultana HP. 2018. A machine learning framework for feature selection in heart disease classification using improved particle swarm optimization with support vector machine classifier. Program Comput Software. 44(6):388–397. doi:https://doi.org/10.1134/S0361768818060129.
- Weinkauf CC, Concha-Moore K, Lindner JR, Marinelli ER, Hadinger KP, Bhattacharjee S, Berman SS, Goshima K, Leon LR Jr, Matsunaga TO, et al. 2018. Endothelial vascular cell adhesion molecule 1 is a marker for high-risk carotid plaques and target for ultrasound molecular imaging. J Vasc Surg. 68(6):105S–13S. doi:https://doi.org/10.1016/j.jvs.2017.10.088.