Pathology tests using artificial intelligence (AI) to characterize tissue samples can accurately predict clinically significant progression of prostate cancer after surgery, according to recent studies.
Artificial intelligence has broad application prospects in the field of prostate cancer. In fact, more and more scientists are devoting themselves to AI-related prostate cancer research. However, more cooperation between different countries and institutions would be beneficial. Since it could expedite the research, resulting in the development of AI-powered predictive technology sooner.
Scientists expect the use of deep learning technology for non-invasive diagnosis and precise minimally invasive treatment will continue to be the focus of research in the next few years.
Applications of AI in predictive analytics
AI has been developing rapidly and shows great promise in the medical field. Researchers are already using it widely for diagnosis and prognosis predictions for varying types of cancer. This, of course, includes prostate cancer too.
Artificial intelligence has broad prospects in the precise diagnosis and treatment of prostate cancer.
For example, we already have RadClip. A newly developed artificial intelligence tool that shows great potential for the prediction of prostate cancer aggressiveness. It can also predict how likely it is for a prostate cancer patient to relapse after surgery. That is to say, it can do so more accurately than the currently available standards.
Research has shown that RadClip should lead to more effective and targeted treatment. Leading to less invasive treatments for prostate cancer.
Artificial intelligence could predict prostate cancer relapses post-surgery
Prostate cancer recurrence is usually treatable. It can even heal. The treatment following a recurrence can differ, however. Unfortunately, in approximately 30% of patients, PSA levels rise again after surgery. It’s known as biochemical recurrence and can indicate the regrowth of prostate cancer cells.
Biochemical recurrence is a prognostic indicator of eventual progression to clinical metastasis and death from prostate cancer. Estimating the likelihood of biochemical recurrence can help to better stratify patients for specific adjuvant therapy.
On the other hand, Long-term follow-up is needed to detect the recurrence of prostate cancer. Current data includes a follow-up period of up to 13 years, although a short average of only four years.
And that’s where new AI predictive models could come in. Expediting this process and getting patients with recurring prostate cancer the right treatment sooner.
Finding out your cancer has returned can bring back some complex feelings and returning emotions. Joining a prostate cancer support group can really help to support you through this process.
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Check our resources section for further information. Where we can even help you connect with a prostate cancer survivor.
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