A scoping review of the 2019–2021 scientiC discourse on machine learning in medical imaGING
The boundaries between strengths and challenges, with cross-cutting ethical and regulatory implications, remain blurred. The literature emphasizes explainability and trustworthiness, with a largely missing discussion about the specific technical and regulatory challenges surrounding these concepts. Future trends are expected to shift towards multi-source models, combining imaging with an array of other data, in a more open access, and explainable manner.
Beyond high hopes: A scoping review of the 2019–2021 scientific discourse on machine learning in medical imaging | PLOS Digital Health