{"title":"Application of artificial intelligence and machine learning techniques in\u0000 supporting the diagnosis and treatment of neurological diseases","authors":"K. Belowska-Bień, B. Bień","doi":"10.15557/an.2021.0021","DOIUrl":"https://doi.org/10.15557/an.2021.0021","url":null,"abstract":"The first two decades of the 21st century have seen great advances in artificial\u0000 intelligence and machine learning. The techniques have found their way into everyday\u0000 life, for example in smartphones, search engines, digital customer assistants, motion\u0000 control systems, and biomedical devices. The aims of this paper are to outline the\u0000 possibilities for using artificial intelligence and machine learning techniques in\u0000 supporting the diagnosis and treatment of neurological diseases, and to discuss selected\u0000 applications of these techniques based on the most recent published reports. First,\u0000 contemporary definitions of artificial intelligence and machine learning are presented.\u0000 This is followed by a review of the most important techniques for intelligent data\u0000 processing: search methods, mathematical logic, probabilistic methods, classifiers, and\u0000 artificial neural networks (including deep and convolutional networks). Areas of\u0000 application of these techniques in medicine are identified, including disease diagnosis\u0000 and support of treatment as well as monitoring and prediction of changes in health\u0000 status. The role of artificial intelligence and machine learning in neuroscience is\u0000 presented, together with examples of diagnostic applications based on anatomical,\u0000 morphological and functional brain connectivity data. Sample applications of intelligent\u0000 techniques in supporting the treatment (including surgical management) of nervous system\u0000 diseases are also described. Ambient smart devices monitoring the health status of\u0000 patients with chronic neurological conditions are discussed, and selected projects based\u0000 on smart techniques to support early detection of symptoms of neurodegenerative\u0000 disorders are described. The conclusions highlight the potential of the techniques, as\u0000 well as the challenges and risks associated with them. A possible synergy between\u0000 intelligent systems and actions taken by medical staff is outlined as a way to improve\u0000 the safety and quality of life of patients with acute and chronic neurological\u0000 diseases.","PeriodicalId":41161,"journal":{"name":"Aktualnosci Neurologiczne","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47498744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}