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Multimodal Data Integration to Predict Severe Acute Oral Mucositis of Nasopharyngeal Carcinoma Patients Following Radiation Therapy.
Dong, Yanjing; Zhang, Jiang; Lam, Saikt; Zhang, Xinyu; Liu, Anran; Teng, Xinzhi; Han, Xinyang; Cao, Jin; Li, Hongxiang; Lee, Francis Karho; Yip, Celia Waiyi; Au, Kwokhung; Zhang, Yuanpeng; Cai, Jing.
Afiliação
  • Dong Y; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China.
  • Zhang J; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China.
  • Lam S; Research Institute for Smart Ageing, The Hong Kong Polytechnic University, Hong Kong SAR, China.
  • Zhang X; Department of Biomedical Engineering, Faculty of Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China.
  • Liu A; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China.
  • Teng X; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China.
  • Han X; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China.
  • Cao J; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China.
  • Li H; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China.
  • Lee FK; Department of Radiology, Fujian Medical University Union Hospital, Fujian Medical University, Fuzhou 350000, China.
  • Yip CW; Department of Clinical Oncology, Queen Elizabeth Hospital, Hong Kong SAR, China.
  • Au K; Department of Clinical Oncology, Queen Elizabeth Hospital, Hong Kong SAR, China.
  • Zhang Y; Department of Clinical Oncology, Queen Elizabeth Hospital, Hong Kong SAR, China.
  • Cai J; Department of Medical Informatics, Nantong University, Nantong 226000, China.
Cancers (Basel) ; 15(7)2023 Mar 29.
Article em En | MEDLINE | ID: mdl-37046693
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Prognostic_studies / Risk_factors_studies Aspecto: Patient_preference Idioma: En Revista: Cancers (Basel) Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Prognostic_studies / Risk_factors_studies Aspecto: Patient_preference Idioma: En Revista: Cancers (Basel) Ano de publicação: 2023 Tipo de documento: Article