Methodological Issues in Evaluating Machine Learning Models for EEG Seizure Prediction: Good Cross-Validation Accuracy Does Not Guarantee Generalization to New Patients.
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| Title: | Methodological Issues in Evaluating Machine Learning Models for EEG Seizure Prediction: Good Cross-Validation Accuracy Does Not Guarantee Generalization to New Patients. |
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| Authors: | Shafiezadeh, Sina1, sina.shafiezadeh@studenti.unipd.it, Duma, Gian Marco2, Mento, Giovanni1,3, Danieli, Alberto2, Antoniazzi, Lisa2, Del Popolo Cristaldi, Fiorella1, Bonanni, Paolo2, Testolin, Alberto1,4, sina.shafiezadeh@studenti.unipd.it |
| Source: | Applied Sciences (2076-3417); Apr2023, Vol. 13 Issue 7, p4262, 12p |
| Database: | Applied Science & Technology Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 163038147 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=163038147 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/app13074262 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 4262 Titles: – TitleFull: Methodological Issues in Evaluating Machine Learning Models for EEG Seizure Prediction: Good Cross-Validation Accuracy Does Not Guarantee Generalization to New Patients. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Shafiezadeh, Sina – PersonEntity: Name: NameFull: Duma, Gian Marco – PersonEntity: Name: NameFull: Mento, Giovanni – PersonEntity: Name: NameFull: Danieli, Alberto – PersonEntity: Name: NameFull: Antoniazzi, Lisa – PersonEntity: Name: NameFull: Del Popolo Cristaldi, Fiorella – PersonEntity: Name: NameFull: Bonanni, Paolo – PersonEntity: Name: NameFull: Testolin, Alberto IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2023 Type: published Y: 2023 Identifiers: – Type: issn-print Value: 20763417 Numbering: – Type: volume Value: 13 – Type: issue Value: 7 Titles: – TitleFull: Applied Sciences (2076-3417) Type: main |
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