Correction: Machine learning-based normal tissue complication probability model for predicting albumin-bilirubin (ALBI) grade increase in hepatocellular carcinoma patients
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2023-03-01
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| Series: | Radiation Oncology |
| Online Access: | https://doi.org/10.1186/s13014-023-02212-9 |
| _version_ | 1797863947074797568 |
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| author | Anussara Prayongrat Natchalee Srimaneekarn Kanokporn Thonglert Chonlakiet Khorprasert Napapat Amornwichet Petch Alisanant Hiroki Shirato Keiji Kobashi Sira Sriswasdi |
| author_facet | Anussara Prayongrat Natchalee Srimaneekarn Kanokporn Thonglert Chonlakiet Khorprasert Napapat Amornwichet Petch Alisanant Hiroki Shirato Keiji Kobashi Sira Sriswasdi |
| author_sort | Anussara Prayongrat |
| collection | DOAJ |
| first_indexed | 2024-04-09T22:43:47Z |
| format | Article |
| id | doaj.art-69278e8ef1534f3cad3c686bd650e411 |
| institution | Directory Open Access Journal |
| issn | 1748-717X |
| language | English |
| last_indexed | 2024-04-09T22:43:47Z |
| publishDate | 2023-03-01 |
| publisher | BMC |
| record_format | Article |
| series | Radiation Oncology |
| spelling | doaj.art-69278e8ef1534f3cad3c686bd650e4112023-03-22T11:58:15ZengBMCRadiation Oncology1748-717X2023-03-011811110.1186/s13014-023-02212-9Correction: Machine learning-based normal tissue complication probability model for predicting albumin-bilirubin (ALBI) grade increase in hepatocellular carcinoma patientsAnussara Prayongrat0Natchalee Srimaneekarn1Kanokporn Thonglert2Chonlakiet Khorprasert3Napapat Amornwichet4Petch Alisanant5Hiroki Shirato6Keiji Kobashi7Sira Sriswasdi8Division of Radiation Oncology, Department of Radiology, Faculty of Medicine, Chulalongkorn UniversityDepartment of Anatomy, Faculty of Dentistry, Mahidol UniversityDivision of Radiation Oncology, Department of Radiology, Faculty of Medicine, Chulalongkorn UniversityDivision of Radiation Oncology, Department of Radiology, Faculty of Medicine, Chulalongkorn UniversityDivision of Radiation Oncology, Department of Radiology, Faculty of Medicine, Chulalongkorn UniversityDivision of Radiation Oncology, Department of Radiology, Faculty of Medicine, Chulalongkorn UniversityGraduate School of Biomedical Science and Engineering, Hokkaido UniversityDepartment of Medical Physics, Hokkaido University HospitalResearch Affairs, Faculty of Medicine, Chulalongkorn Universityhttps://doi.org/10.1186/s13014-023-02212-9 |
| spellingShingle | Anussara Prayongrat Natchalee Srimaneekarn Kanokporn Thonglert Chonlakiet Khorprasert Napapat Amornwichet Petch Alisanant Hiroki Shirato Keiji Kobashi Sira Sriswasdi Correction: Machine learning-based normal tissue complication probability model for predicting albumin-bilirubin (ALBI) grade increase in hepatocellular carcinoma patients Radiation Oncology |
| title | Correction: Machine learning-based normal tissue complication probability model for predicting albumin-bilirubin (ALBI) grade increase in hepatocellular carcinoma patients |
| title_full | Correction: Machine learning-based normal tissue complication probability model for predicting albumin-bilirubin (ALBI) grade increase in hepatocellular carcinoma patients |
| title_fullStr | Correction: Machine learning-based normal tissue complication probability model for predicting albumin-bilirubin (ALBI) grade increase in hepatocellular carcinoma patients |
| title_full_unstemmed | Correction: Machine learning-based normal tissue complication probability model for predicting albumin-bilirubin (ALBI) grade increase in hepatocellular carcinoma patients |
| title_short | Correction: Machine learning-based normal tissue complication probability model for predicting albumin-bilirubin (ALBI) grade increase in hepatocellular carcinoma patients |
| title_sort | correction machine learning based normal tissue complication probability model for predicting albumin bilirubin albi grade increase in hepatocellular carcinoma patients |
| url | https://doi.org/10.1186/s13014-023-02212-9 |
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