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Kunstig intelligens til klinisk billeddiagnostik

Forfatter(e)

Claes Nøhr Ladefoged, Flemming Littrup Andersen, & Liselotte Højgaard

Klinik for Klinisk Fysiologi, Nuklearmedicin & PET, Rigshospitalet

Ugeskr Læger 2020;182:V10190563

Reference: 
UgeskrLæger 2020;182: V10190563
Artificial intelligence for diagnostic imaging

Claes Nøhr Ladefoged, Flemming Littrup Andersen, & Liselotte Højgaard

Ugeskr Læger 2020;182:V10190563

Artificial intelligence (AI) is a computer-based system, which in diagnostic imaging can improve patient flow, optimise image processing, shorten scan time, reduce radiation dose and be used as decision aid in image interpretation. In this review, we argue that AI algorithms should be based on evidence with initial hypothesis, then a choice of algorithm and development with training on the initial data set; afterwards the algorithms should be tested on a new representative dataset, and finally it should be tested in a prospective study. If the AI is evidence-based and can solve a task better or cheaper than the usual methodology, it can be implemented.

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