Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review
2016·895 Zitationen·Journal of the American Medical Informatics AssociationOpen Access
Volltext beim Verlag öffnen895
Zitationen
4
Autoren
2016
Jahr
Abstract
EHR data present both opportunities and challenges for clinical risk prediction. There is room for improvement in designing such studies.
Ähnliche Arbeiten
"Why Should I Trust You?"
2016 · 14.588 Zit.
A Comprehensive Survey on Graph Neural Networks
2020 · 8.861 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.423 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.917 Zit.
Artificial intelligence in healthcare: past, present and future
2017 · 4.494 Zit.
Autoren
Institutionen
Themen
Machine Learning in HealthcareChronic Disease Management StrategiesElectronic Health Records Systems