چکیده مقاله
Introduction: Multiple Sclerosis MS is a prevalent autoimmune and inflammatorydisorder that leaves demyelination and neurodegenerative changes in Central NervousSystem CNS The retina is among the body organs that are affected by MS, OpticalCoherence Tomography OCT images can play a key role in the preliminary stages Artificial intelligence based methods are commonly applied in image classification andhave shown promising and applicable results in MS diagnosis Method: In total, more than 197 MS patients and more than 283 healthy patients wereincluded in this study, and Spectralis OCT images were taken, and artificial intelligencewas trained with several thousand images using data augmentation Finally, theautomatic diagnosis algorithm of MS disease was implemented, and then the diagramof network loss processes was drawn and the sensitivity, specificity and accuracy of thealgorithm were evaluated Result: The disease was successfully diagnosed by OCT images with an accuracy of93 0 Conclusion: The proposed method showed improvements in early stage MS diagnosis and with the potentiality to be used in either the diagnosis or prediction of the progression of other diseases that affect the CNS e g Alzheimer's disease, bipolar disorder, etc
کلیدواژهها
نویسندگان
Ali Mehravar
Department of Medical Bioengineering, Faculty of Advanced Medical Sciences, Tabriz University of MedicalSciences, Tabriz, Iran Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran
Samaneh Hoseini
Neurosciences Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
Yashar Amizadeh
Ophthalmic Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Seyed Hossein Rasta
Department of Medical Physics, Tabriz University of Medical Sciences, Tabriz, Iran School of Medical Sciences, University of Aberdeen, Aberdeen, UK
شیوه ارجاع
Mehravar, Ali and Hoseini, Samaneh and Amizadeh, Yashar and Rasta, Seyed Hossein,1402,Assessment and diagnosis of multiple sclerosis using optical coherencetomography with the help of artificial intelligence and convolutional neuralnetworks in Python.,The 15th International Conference on Innovation and Research in Engineering Sciences
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