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Using artificial intelligence to reduce queuing time and improve satisfaction in pediatric outpatient service: A randomized clinical trial.
Li, Xiaoqing; Tian, Dan; Li, Weihua; Hu, Yabin; Dong, Bin; Wang, Hansong; Yuan, Jiajun; Li, Biru; Mei, Hao; Tong, Shilu; Zhao, Liebin; Liu, Shijian.
Afiliação
  • Li X; School of Medicine, Shanghai Children's Medical Center, Child Health Advocacy Institute, Shanghai Jiao Tong University, Shanghai, China.
  • Tian D; School of Public Health, Shanghai Jiao Tong University, Shanghai, China.
  • Li W; Division of Hospital Management, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Hu Y; Pediatric AI Clinical Application and Research Center, Shanghai Children's Medical Center, Shanghai, China.
  • Dong B; Shanghai Engineering Research Center of Intelligence Pediatrics (SERCIP), Shanghai, China.
  • Wang H; Division of Hospital Management, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Yuan J; Pediatric AI Clinical Application and Research Center, Shanghai Children's Medical Center, Shanghai, China.
  • Li B; Shanghai Engineering Research Center of Intelligence Pediatrics (SERCIP), Shanghai, China.
  • Mei H; School of Medicine, Shanghai Children's Medical Center, Child Health Advocacy Institute, Shanghai Jiao Tong University, Shanghai, China.
  • Tong S; Division of Hospital Management, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Zhao L; Pediatric AI Clinical Application and Research Center, Shanghai Children's Medical Center, Shanghai, China.
  • Liu S; Shanghai Engineering Research Center of Intelligence Pediatrics (SERCIP), Shanghai, China.
Front Pediatr ; 10: 929834, 2022.
Article em En | MEDLINE | ID: mdl-36034568
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials Idioma: En Revista: Front Pediatr Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials Idioma: En Revista: Front Pediatr Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China