Can artificial intelligence help clinicians in prostate cancer screening?
To mitigate the drawbacks of PSA screening, serial PSA testing procedures have been introduced. PSA velocity and PSA doubling time measure the change of PSA level over time, making it easier for clinicians to detect a sudden rise in PSA levels. It is clearly a step towards a more personalized detection test. Yet those types of measurements are based on an over-simplification of a complex movement. PSA levels fluctuate up and down. Some causes of variation in PSA levels, outside of prostate cancer, have been identified such as climate, ejaculation, vigorous bike riding, etc. but some remain unexplained. PSA levels thus fluctuate randomly.
A non-random pattern can be detected by Artificial Intelligence (AI) tests long before a human clinician can even suspect it.
We propose to apply a non-randomness AI detection test to time series of PSA levels to determine whether it can help in detecting PSA cancers early without running the risk of overdiagnosis.
Check wether AI test can find cancer or abnormality in patients with cancer (sensitivity)
Check wether Ai test can give negative results in patients with no cancer (specificity)
Check wether AI test can discriminate amongst fast and slow growing cancers
Brian DeWitt
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Development and validation of an imageless machine-learning algorithm for the initial screening of prostate cancer.
Martelin N, De Witt B, Chen B, Eschwège P
Prostate. 2024 Apr 4 PUBMED