한국과학기술연구원(KIST)

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Noninvasive Precision Screening of Prostate Cancer by Urinary Multimarker Sensor and Artificial Intelligence Analysis
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Abstract

Screening for prostate cancer relies on the serum prostate-specific antigen test, which provides a high rate of false positives (80%). This results in a large number of unnecessary biopsies and subsequent overtreatment. Considering the frequency of the test, there is a critical unmet need of precision screening for prostate cancer. Here, we introduced a urinary multimarker biosensor with a capacity to learn to achieve this goal. The correlation of clinical state with the sensing signals from urinary multimarkers was analyzed by two common machine learning algorithms. As the number of biomarkers was increased, both algorithms provided a monotonic increase in screening performance. Under the best combination of biomarkers, the machine learning algorithms screened prostate cancer patients with more than 99% accuracy using 76 urine specimens. Urinary multimarker biosensor leveraged by machine learning analysis can be an important strategy of precision screening for cancers using a drop of bodily fluid.

KEYWORDS: cancer screening, urine, multimarker, artificial intelligence, prostate cancer

주소복사
논문정보   
- 형식: Research article
- 게재일: 2020년 12월 (BRIC 등록일 2020-12-22)
- 연구진: 국내연구진태극기
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