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From computer to bedside, involving neonatologists in artificial intelligence models for neonatal medicine.
Vijlbrief, Daniel; Dudink, Jeroen; van Solinge, Wouter; Benders, Manon; Haitjema, Saskia.
Affiliation
  • Vijlbrief D; Department of Neonatology, University Medical Center Utrecht, Utrecht University, UMC Utrecht, Utrecht, The Netherlands. D.C.Vijlbrief@umcutrecht.nl.
  • Dudink J; Department of Neonatology, University Medical Center Utrecht, Utrecht University, UMC Utrecht, Utrecht, The Netherlands.
  • van Solinge W; Central Diagnostic Laboratory, University Medical Center Utrecht, Utrecht University, UMC Utrecht, Utrecht, The Netherlands.
  • Benders M; Department of Neonatology, University Medical Center Utrecht, Utrecht University, UMC Utrecht, Utrecht, The Netherlands.
  • Haitjema S; Central Diagnostic Laboratory, University Medical Center Utrecht, Utrecht University, UMC Utrecht, Utrecht, The Netherlands.
Pediatr Res ; 93(2): 437-439, 2023 01.
Article in En | MEDLINE | ID: mdl-36526854
In recent years, data have become the main driver of medical innovation. With increased availability and decreased price of storage and computing power, the potential for improvement in care is enormous. Many data-driven explorations have started. However, the actual implementation of artificial intelligence in healthcare remains scarce. We describe essential elements during a computer-to-bedside process in a data science project that support the crucial role of the neonatologist. IMPACT: There is a great potential for data science in neonatal medicine. Multidisciplinary teams form the foundation of a data science project. Domain experts will need to play a pivotal role. We need an open learning environment.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Medicine Limits: Humans / Newborn Language: En Journal: Pediatr Res Year: 2023 Document type: Article Affiliation country: Netherlands Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Medicine Limits: Humans / Newborn Language: En Journal: Pediatr Res Year: 2023 Document type: Article Affiliation country: Netherlands Country of publication: United States