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Artificial intelligence innovation in healthcare: Relevance of reporting guidelines for clinical translation from bench to bedside
7
Zitationen
20
Autoren
2023
Jahr
Abstract
Artificial intelligence (AI) and digital innovation are transforming healthcare. Technologies such as machine learning in image analysis, natural language processing in medical chatbots and electronic medical record extraction have the potential to improve screening, diagnostics and prognostication, leading to precision medicine and preventive health. However, it is crucial to ensure that AI research is conducted with scientific rigour to facilitate clinical implementation. Therefore, reporting guidelines have been developed to standardise and streamline the development and validation of AI technologies in health. This commentary proposes a structured approach to utilise these reporting guidelines for the translation of promising AI techniques from research and development into clinical translation, and eventual widespread implementation from bench to bedside.
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Autoren
Institutionen
- Singapore National Eye Center(SG)
- Singapore Eye Research Institute(SG)
- Singapore General Hospital(SG)
- Duke-NUS Medical School(SG)
- National University of Singapore(SG)
- National Heart Centre Singapore(SG)
- Bioinformatics Institute(SG)
- Agency for Science, Technology and Research(SG)
- Institute of High Performance Computing(SG)
- Ministry of Health(SG)
- National University Health System(SG)
- Singapore Clinical Research Institute(SG)
- Health Sciences Authority(SG)
- SingHealth(SG)