Prostate cancer detection software: what to think about before you buy: 2024 (1) Update
Автор: anwar padhani
Загружено: 2024-05-18
Просмотров: 280
Presented at the BSUR in Manchester 2024 (1)
New data is constantly appearing so I will update this later this year.
Learning objectives:
To acquire knowledge of the essential diagnostic performance characteristics when choosing AI software for MRI-based prostate cancer detection
To comprehend the differences between a radiologist's diagnostic assistant and a biopsy management tool
Learning points:
Adequately trained and tested DLA-CAD systems can assist in workload reduction, and meet the increasing demand for prostate MRI
=Current software delivers average-trained MDT radiologists’ performance with average levels of false alarms/false reassurances
=Current role is to improve the consistency of MRI reporting and aid in biopsy-management tasks
There is a lack of prospective multicentric, multivendor validation data and data on MDT care/deployment into clinical practice
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