Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Doctors in Medical Data Sciences: A New Curriculum (Preprint)
0
Zitationen
3
Autoren
2021
Jahr
Abstract
<sec> <title>UNSTRUCTURED</title> Machine Learning (ML), a branch of Artificial Intelligence, now competes with human experts in many specialized biomedical fields and will play an increasing role in precision medicine. As with any other technological advance in medicine, the keys to understanding must be integrated into practitioner training. To respond to this challenge, this viewpoint discusses some necessary changes in the health studies curriculum to help practitioners interpret decisions made by a machine and question them in relation to the patient's medical context. The complexity of technology and the inherent criticality of its use in medicine also necessitate a new medical profession. To achieve this objective, this viewpoint will propose new medical practitioners, with skills both in medicine and in data science, The Doctor in Medical Data Sciences. </sec>
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.393 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.259 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.688 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.502 Zit.