Your browser doesn't support javascript.
loading
Using Artificial Intelligence for the Early Detection of Micro-Progression of Pressure Injuries in Hospitalized Patients: A Preliminary Nursing Perspective Evaluation.
Wu, Shu-Chen; Li, Yu-Chuan Jack; Chen, Hsiao-Ling; Ku, Mei Ling; Yu, Yen-Chen; Nguyen, Phung-Anh; Huang, Chih-Wei.
Afiliación
  • Wu SC; Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.
  • Li YJ; Department of Nursing, Far Eastern Memorial Hospital, New Taipei City, Taiwan.
  • Chen HL; Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.
  • Ku ML; International Center for Health Information Technology, Taipei Medical University, Taipei, Taiwan.
  • Yu YC; Department of Nursing, Far Eastern Memorial Hospital, New Taipei City, Taiwan.
  • Nguyen PA; Department of Nursing, Far Eastern Memorial Hospital, New Taipei City, Taiwan.
  • Huang CW; Plastic Reconstructive Aesthetic Surgery, Far Eastern Memorial Hospital, New Taipei City, Taiwan.
Stud Health Technol Inform ; 290: 1016-1017, 2022 Jun 06.
Article en En | MEDLINE | ID: mdl-35673183
This study established a predictive model for the early detection of micro-progression of pressure injuries (PIs) from the perspective of nurses. An easy and programing-free artificial intelligence modeling tool with professional evaluation capability and it performed independently by nurses was used for this purpose. In the preliminary evaluation, the model achieved an accuracy of 89%. It can bring positive benefits to clinical care. Only the overfitting issue and image subtraction method remain to be addressed.
Asunto(s)
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Úlcera por Presión Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Límite: Humans Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2022 Tipo del documento: Article País de afiliación: Taiwán Pais de publicación: Países Bajos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Úlcera por Presión Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Límite: Humans Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2022 Tipo del documento: Article País de afiliación: Taiwán Pais de publicación: Países Bajos