The set of sensor signals collected for each patient was then analyzed using ML to examine the patient for PCa. Seventy-six urine samples were measured three times, generating 912 biomarker signals or 228 sets of sense signals. We used RF and NN algorithms to analyze the multi-marking signals. Both algorithms provided increased accuracy, and the AUROC increased in size as the number of biomarkers increased. Credit: Korea Institute of Science and Technology (KIST)
Prostate cancer is one of the most common cancers among men. Patients are determined to have prostate cancer, mainly based on PSA, a cancer factor in blood. Because the diagnostic accuracy is as low as 30%, a significant number of patients undergo additional invasive biopsy and therefore suffer from side effects, such as bleeding and pain.
The Korean Institute of Science and Technology (KIST) announced that the collaborative research team led by Dr Kwan Hyi Lee of the Biomaterials Research Center and Professor In Gab Jeong of Asan Medical Center developed a technique to remove prostate cancer from urine within just 20 minutes. to diagnose. with almost 100% accuracy. The research team developed this technique by introducing a clever AI analysis method to an ultrasensitive biosensor on electrical signal.
As a non-invasive method, a diagnostic test using urine is convenient for patients and it is not necessary to do invasive biopsy, whereby cancer is diagnosed without side effects. Because the concentration of cancer factors is low in urine, biosensors on urine are only used to classify risk groups rather than to diagnose them accurately so far.
Dr. Lee’s team at the KIST is working on the development of a technique for diagnosing urinary tract diseases using an ultrasensitive biosensor based on electrical signal. A single cancer factor approach associated with a cancer diagnosis was limited to increasing diagnostic accuracy to more than 90%. To overcome this limitation, however, the team simultaneously used different types of cancer factors instead of using only one to innovatively improve diagnostic accuracy.
The team has developed an ultrasensitive semiconductor sensor system that can simultaneously detect trace amounts of four selected cancer factors in urine for the diagnosis of prostate cancer. They trained AI using the correlation between the four cancer factors, obtained from the developed sensor. The trained AI algorithm was then used to identify those with prostate cancer by analyzing complex patterns of the detected signals. The diagnosis of prostate cancer using the AI analysis successfully detected 76 urine samples with almost 100 percent accuracy.
“For patients in need of surgery and / or treatments, cancer can be diagnosed with high accuracy by using urine to reduce unnecessary biopsy and treatments, which can dramatically reduce medical costs and medical staff exhaustion,” Professor Jeong told Asan Medical Center said. “This research has developed a smart biosensor that can quickly diagnose prostate cancer with almost 100 percent accuracy only through a urine test, and it can be further used in the accurate diagnosis of other cancers via a urine test,” said Dr. Lee said at the KIST. .
Stop smoking, your bladder will thank you
Hojun Kim et al., Non-invasive precision examination of prostate cancer by multi-marker urinary sensor and artificial intelligence analysis, ACS Nano (2020). DOI: 10.1021 / acsnano.0c06946
Provided by the National Research Council for Science and Technology
Quotation: Cancer can be accurately diagnosed using an artificial intelligence urine test (2021, January 21) detected on January 21, 2021 from https://phys.org/news/2021-01-cancer-precisely-urine-artificial-intelligence .html
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