Development and Validation of a Machine Learning Model to Predict Oral Anticoagulant Use in Stroke From Prothrombin Time-International Normalized Ratio and Activated Partial Thromboplastin Time.
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| Title: | Development and Validation of a Machine Learning Model to Predict Oral Anticoagulant Use in Stroke From Prothrombin Time-International Normalized Ratio and Activated Partial Thromboplastin Time. |
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| Authors: | Fujiwara G; Department of Neurosurgery Kyoto Prefectural University of Medicine Kyoto Japan.; Department of Neurosurgery Japanese Red Cross Kyoto Daini Hospital Kyoto Japan., Nagakane Y; Department of Neurology Japanese Red Cross Kyoto Daini Hospital Kyoto Japan., Murakami N; Department of Neurosurgery Japanese Red Cross Kyoto Daini Hospital Kyoto Japan., Suehiro E; Department of Neurosurgery International University of Health and Welfare School of Medicine Chiba Japan., Hashimoto N; Department of Neurosurgery Kyoto Prefectural University of Medicine Kyoto Japan., Yoshimura S; Department of Cerebrovascular Medicine National Cerebral and Cardiovascular Center Suita Japan., Toyoda K; Department of Cerebrovascular Medicine National Cerebral and Cardiovascular Center Suita Japan., Okada Y; Department of Preventive Services, School of Public Health Kyoto University Kyoto Japan.; Pre-hospital and Emergency Research Centre, Health Services Research and Population Health Duke-NUS Medical School, National University of Singapore Singapore. |
| Source: | Journal of the American Heart Association [J Am Heart Assoc] 2026 Apr 07; Vol. 15 (7), pp. e047432. Date of Electronic Publication: 2026 Mar 18. |
| Publication Type: | Journal Article; Validation Study; Multicenter Study |
| Journal Info: | Publisher: Wiley-Blackwell Country of Publication: England NLM ID: 101580524 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2047-9980 (Electronic) Linking ISSN: 20479980 NLM ISO Abbreviation: J Am Heart Assoc Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 41848031 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Development and Validation of a Machine Learning Model to Predict Oral Anticoagulant Use in Stroke From Prothrombin Time-International Normalized Ratio and Activated Partial Thromboplastin Time. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Fujiwara+G%22">Fujiwara G</searchLink>; Department of Neurosurgery Kyoto Prefectural University of Medicine Kyoto Japan.; Department of Neurosurgery Japanese Red Cross Kyoto Daini Hospital Kyoto Japan.<br /><searchLink fieldCode="AU" term="%22Nagakane+Y%22">Nagakane Y</searchLink>; Department of Neurology Japanese Red Cross Kyoto Daini Hospital Kyoto Japan.<br /><searchLink fieldCode="AU" term="%22Murakami+N%22">Murakami N</searchLink>; Department of Neurosurgery Japanese Red Cross Kyoto Daini Hospital Kyoto Japan.<br /><searchLink fieldCode="AU" term="%22Suehiro+E%22">Suehiro E</searchLink>; Department of Neurosurgery International University of Health and Welfare School of Medicine Chiba Japan.<br /><searchLink fieldCode="AU" term="%22Hashimoto+N%22">Hashimoto N</searchLink>; Department of Neurosurgery Kyoto Prefectural University of Medicine Kyoto Japan.<br /><searchLink fieldCode="AU" term="%22Yoshimura+S%22">Yoshimura S</searchLink>; Department of Cerebrovascular Medicine National Cerebral and Cardiovascular Center Suita Japan.<br /><searchLink fieldCode="AU" term="%22Toyoda+K%22">Toyoda K</searchLink>; Department of Cerebrovascular Medicine National Cerebral and Cardiovascular Center Suita Japan.<br /><searchLink fieldCode="AU" term="%22Okada+Y%22">Okada Y</searchLink>; Department of Preventive Services, School of Public Health Kyoto University Kyoto Japan.; Pre-hospital and Emergency Research Centre, Health Services Research and Population Health Duke-NUS Medical School, National University of Singapore Singapore. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101580524%22">Journal of the American Heart Association</searchLink> [J Am Heart Assoc] 2026 Apr 07; Vol. 15 (7), pp. e047432. <i>Date of Electronic Publication: </i>2026 Mar 18. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article; Validation Study; Multicenter Study – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Wiley-Blackwell%22">Wiley-Blackwell </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101580524 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2047-9980 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2220479980%22">20479980 </searchLink><i>NLM ISO Abbreviation: </i>J Am Heart Assoc <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41848031 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1161/JAHA.125.047432 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: e047432 Titles: – TitleFull: Development and Validation of a Machine Learning Model to Predict Oral Anticoagulant Use in Stroke From Prothrombin Time-International Normalized Ratio and Activated Partial Thromboplastin Time. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Fujiwara G – PersonEntity: Name: NameFull: Nagakane Y – PersonEntity: Name: NameFull: Murakami N – PersonEntity: Name: NameFull: Suehiro E – PersonEntity: Name: NameFull: Hashimoto N – PersonEntity: Name: NameFull: Yoshimura S – PersonEntity: Name: NameFull: Toyoda K – PersonEntity: Name: NameFull: Okada Y IsPartOfRelationships: – BibEntity: Dates: – D: 07 M: 04 Text: 2026 Apr 07 Type: published Y: 2026 Identifiers: – Type: issn-electronic Value: 2047-9980 Numbering: – Type: volume Value: 15 – Type: issue Value: 7 Titles: – TitleFull: Journal of the American Heart Association Type: main |
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