Please use this identifier to cite or link to this item:
https://dspace.ffh.bg.ac.rs/handle/123456789/2165| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Mitrović, Katarina | en_US |
| dc.contributor.author | Savić, Andrej M | en_US |
| dc.contributor.author | Radojičić, Aleksandra | en_US |
| dc.contributor.author | Daković, Marko | en_US |
| dc.contributor.author | Petrušić, Igor | en_US |
| dc.date.accessioned | 2024-01-06T18:01:01Z | - |
| dc.date.available | 2024-01-06T18:01:01Z | - |
| dc.date.issued | 2023-12-18 | - |
| dc.identifier.uri | https://dspace.ffh.bg.ac.rs/handle/123456789/2165 | - |
| dc.description.abstract | Previous studies have developed the Migraine Aura Complexity Score (MACS) system. MACS shows great potential in studying the complexity of migraine with aura (MwA) pathophysiology especially when implemented in neuroimaging studies. The use of sophisticated machine learning (ML) algorithms, together with deep profiling of MwA, could bring new knowledge in this field. We aimed to test several ML algorithms to study the potential of structural cortical features for predicting the MACS and therefore gain a better insight into MwA pathophysiology. | en_US |
| dc.language.iso | en | en_US |
| dc.relation | 451-03-47/2023-01/200146 | en_US |
| dc.relation.ispartof | The journal of headache and pain | en_US |
| dc.subject | Artificial intelligence | en_US |
| dc.subject | Machine learning | en_US |
| dc.subject | Magnetic resonance imaging | en_US |
| dc.subject | Migraine with Aura | en_US |
| dc.subject | Prediction, regression | en_US |
| dc.subject | Support vector machine | en_US |
| dc.title | Machine learning approach for Migraine Aura Complexity Score prediction based on magnetic resonance imaging data | en_US |
| dc.type | Journal Article | en_US |
| dc.identifier.doi | 10.1186/s10194-023-01704-z | - |
| dc.identifier.pmid | 38105182 | - |
| dc.relation.grantno | 451-03-47/2023-01/200146 | en_US |
| dc.relation.firstpage | 169 | en_US |
| dc.relation.issue | 1 | en_US |
| dc.relation.volume | 24 | en_US |
| item.fulltext | No Fulltext | - |
| item.openairetype | Journal Article | - |
| item.cerifentitytype | Publications | - |
| item.languageiso639-1 | en | - |
| item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
| item.grantfulltext | none | - |
| crisitem.author.orcid | 0000-0001-7455-5584 | - |
| crisitem.author.orcid | 0000-0002-5412-7328 | - |
| Appears in Collections: | Journal Article | |
SCOPUSTM
Citations
8
checked on Jun 2, 2025
Page view(s)
49
checked on Jun 6, 2025
Google ScholarTM
Check
Altmetric
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.