USING ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN THE MANAGEMENT OF MULTIPLE SCLEROSIS
Multiple Sclerosis is a chronic autoimmune disease characterized by heterogeneous clinical manifestations.. In recent years, the application of artificial ıntelligence methods, particularly machine learning and deep learning techniques, has opened new opportunities for multiple sclerosis manage...
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| Format: | Article |
| Language: | English |
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Information Technology Publishing House
2025-07-01
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| Series: | Problems of Information Society |
| Online Access: | https://jpis.az/uploads/article/en/2025_2/USING_ARTIFICIAL_%C4%B0NTELLIGENCE_TECHNOLOGIES_IN_THE_MANAGEMENT_OF_MULTIPLE_SCLEROSIS.pdf |
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| author | Fatima Aliyeva Aytan Mammadbayli Rana Shiraliyeva |
| author_facet | Fatima Aliyeva Aytan Mammadbayli Rana Shiraliyeva |
| author_sort | Fatima Aliyeva |
| collection | DOAJ |
| description |
Multiple Sclerosis is a chronic autoimmune disease characterized by heterogeneous
clinical manifestations.. In recent years, the application of artificial ıntelligence
methods, particularly machine learning and deep learning techniques, has opened
new opportunities for multiple sclerosis management. In this study, the potential of
artificial ıntelligence for multiple sclerosis diagnostics, treatment and prognosis is
estimated.The research found that RNN models excel in long-term disease
progression modeling by effectively capturing temporal sequences. Random Forest
and XGBoost models accurately predict relapse risks and the probability of disease
progression. The MindGlide platform accelerates MRI analysis, while CDSS
facilitates the optimization of personalized treatment decisions. Biomarker-based
models offer new avenues for early detection of the disease at the subclinical stage.
Overall, hybrid model approaches integrating clinical, radiological, and molecular
data present a promising pathway for personalized multiple sclerosis management
and the development of early intervention strategies. |
| format | Article |
| id | doaj-art-bfc772e3abca4c229c1d18de407ee819 |
| institution | Kabale University |
| issn | 2077-964X 2309-7566 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Information Technology Publishing House |
| record_format | Article |
| series | Problems of Information Society |
| spelling | doaj-art-bfc772e3abca4c229c1d18de407ee8192025-08-20T03:58:44ZengInformation Technology Publishing HouseProblems of Information Society2077-964X2309-75662025-07-01162646910.25045/jpis.v16.i2.08USING ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN THE MANAGEMENT OF MULTIPLE SCLEROSISFatima Aliyevahttps://orcid.org/0000-0001-8392-0838Aytan MammadbayliRana Shiraliyeva Multiple Sclerosis is a chronic autoimmune disease characterized by heterogeneous clinical manifestations.. In recent years, the application of artificial ıntelligence methods, particularly machine learning and deep learning techniques, has opened new opportunities for multiple sclerosis management. In this study, the potential of artificial ıntelligence for multiple sclerosis diagnostics, treatment and prognosis is estimated.The research found that RNN models excel in long-term disease progression modeling by effectively capturing temporal sequences. Random Forest and XGBoost models accurately predict relapse risks and the probability of disease progression. The MindGlide platform accelerates MRI analysis, while CDSS facilitates the optimization of personalized treatment decisions. Biomarker-based models offer new avenues for early detection of the disease at the subclinical stage. Overall, hybrid model approaches integrating clinical, radiological, and molecular data present a promising pathway for personalized multiple sclerosis management and the development of early intervention strategies.https://jpis.az/uploads/article/en/2025_2/USING_ARTIFICIAL_%C4%B0NTELLIGENCE_TECHNOLOGIES_IN_THE_MANAGEMENT_OF_MULTIPLE_SCLEROSIS.pdf |
| spellingShingle | Fatima Aliyeva Aytan Mammadbayli Rana Shiraliyeva USING ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN THE MANAGEMENT OF MULTIPLE SCLEROSIS Problems of Information Society |
| title | USING ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN THE MANAGEMENT OF MULTIPLE SCLEROSIS |
| title_full | USING ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN THE MANAGEMENT OF MULTIPLE SCLEROSIS |
| title_fullStr | USING ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN THE MANAGEMENT OF MULTIPLE SCLEROSIS |
| title_full_unstemmed | USING ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN THE MANAGEMENT OF MULTIPLE SCLEROSIS |
| title_short | USING ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN THE MANAGEMENT OF MULTIPLE SCLEROSIS |
| title_sort | using artificial intelligence technologies in the management of multiple sclerosis |
| url | https://jpis.az/uploads/article/en/2025_2/USING_ARTIFICIAL_%C4%B0NTELLIGENCE_TECHNOLOGIES_IN_THE_MANAGEMENT_OF_MULTIPLE_SCLEROSIS.pdf |
| work_keys_str_mv | AT fatimaaliyeva usingartificialintelligencetechnologiesinthemanagementofmultiplesclerosis AT aytanmammadbayli usingartificialintelligencetechnologiesinthemanagementofmultiplesclerosis AT ranashiraliyeva usingartificialintelligencetechnologiesinthemanagementofmultiplesclerosis |