Advancements in early cancer diagnosis using blood-based biomarkers and a machine learning approach
DOI:
https://doi.org/10.18203/2320-6012.ijrms20240244Keywords:
Early cancer detection, Blood, ctDNA, Machine learningAbstract
Mutations that promote aberrant cell growth are the root of the condition known as cancer. There are over a hundred distinct forms of cancer that have been identified, with lung, colon, pancreatic, breast, kidney, and prostate cancer being the most prevalent. The likelihood that a patient will survive cancer is significantly improved by early identification. Most techniques used to detect cancer are invasive, which may be painful and uncomfortable for patients and prevent them from seeking treatment. As a result, cancer is frequently discovered only after substantial symptoms have developed and it may then be too late for treatment. In this review, we will discuss several methods for detecting cancer through blood tests, different elements that serve as biomarkers, and machine learning algorithms for predicting outcomes.
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