Abstract
The prostate exam is an early detection tool to prevent prostate cancer and the main diagnostic tools for obtaining signs are generally invasive. This article tries chromatographic signals from the urine of prostate cancer patients and control patients as a non-invasive examination proposal. For this purpose, methodologically, urine samples are taken, digitized in chromatograms, treated with mathematical techniques and classified. The mathematical techniques are time normalization, dead time elimination, baseline correction, noise elimination, and peak alignment. Classification techniques analyze energy, in the domain of time and frequency, and the main components in sedimentation graphs and scores. As a result, the chromatographic signal is characterized and identifies the characteristic curve that represents the signal of prostate cancer patients and control patients. The data structure shows a cluster distribution of 88.88% of the vectors for the control patients. In the case of prostate cancer patients, the distribution of data is in clusters around the area defined by control patients. This characterization demarcates signal classification regions to diagnose possible prostate cancer patients, validating the relationship between the chromatographic signal and cancer.
Highlights
Prostate cancer is one of the cancers that most affects the male gender today; more than 5% of every million people are affected by this disease; In addition, the early detection tools available to prevent it and the main diagnostic instruments to obtain evidence are generally invasive, with the rectal examination and serum concentration of the specific prostate antigen being the best known
It is possible to obtain information on prostate cancer non-invasively through chromatography, a procedure defined as the method by which chemical components are separated from a sample, which is represented by a one-dimensional signal with which it is possible to analyze delay, energy or concentration times; allowing the qualitative and quantitative identification of chemical components based on their distribution for characterization [13]
The sequence of the mathematical techniques of signal processing applied to the chromatograms improved the signal-to-noise ratio is 37.67% for control patients, and in 57.55% for patients with prostate cancer
Summary
Prostate cancer is one of the cancers that most affects the male gender today; more than 5% of every million people are affected by this disease; In addition, the early detection tools available to prevent it and the main diagnostic instruments to obtain evidence are generally invasive, with the rectal examination and serum concentration of the specific prostate antigen being the best known. This article tries urine samples from a chromatographic process to obtain one-dimensional signals, analyzes the differentiating characteristics
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