Why implementing machine learning algorithms in the clinic is not a plug-and-play solution: a simulation study of a machine learning algorithm for acute leukaemia subtype diagnosisResearch in context

Why implementing machine learning algorithms in the clinic is not a plug-and-play solution: a simulation study of a machine learning algorithm for acute leukaemia subtype diagnosisResearch in context

Summary: Background: Artificial intelligence (AI) and machine learning (ML) algorithms have shown great promise in clinical medicine. Despite the increasing number of published algorithms, most remain unvalidated in real-world clinical settings. This study aims to simulate the practical implementat...

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Bibliographic Details
Main Authors: Gernot Pucher, Till Rostalski, Felix Nensa, Jens Kleesiek, Hans Christian Reinhardt, Christopher Martin Sauer
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:EBioMedicine
Subjects:
Machine learning
Artificial intelligence
Real-world evaluation
Clinical implementation
Implementation gap
Online Access:http://www.sciencedirect.com/science/article/pii/S2352396424005620
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