期刊
DIAGNOSTICS
卷 11, 期 3, 页码 -出版社
MDPI
DOI: 10.3390/diagnostics11030514
关键词
artificial intelligence; deep neural networks; colorectal cancer; clinical data; computer aided diagnostic system
资金
- Romanian Ministry of Research and Innovation, CCCDI-UEFISCDI [PN-III-P2-2.1-PED-2019-0844, 323PED/2020]
- New National Excellence Program of the Ministry for Innovation and Technology [UNKP-19-4-OE-64]
Colorectal cancer is a common and lethal tumor globally. A computer aided diagnosis system was designed in this research, using machine learning techniques and achieving significant performance improvement in regression problems.
Colorectal cancer is the third most common and second most lethal tumor globally, causing 900,000 deaths annually. In this research, a computer aided diagnosis system was designed that detects colorectal cancer, using an innovative dataset composing of both numeric (blood and urine analysis) and qualitative data (living environment of the patient, tumor position, T, N, M, Dukes classification, associated pathology, technical approach, complications, incidents, ultrasonography-dimensions as well as localization). The intelligent computer aided colorectal cancer diagnosis system was designed using different machine learning techniques, such as classification and shallow and deep neural networks. The maximum accuracy obtained from solving the binary classification problem with traditional machine learning algorithms was 77.8%. However, the regression problem solved with deep neural networks yielded with significantly better performance in terms of mean squared error minimization, reaching the value of 0.0000529.
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