Ultrasensitive electrochemical detection of clinically relevant genetic mutations via nanoparticle surface localized amplification and machine learning.

Abstract excerpt

Genetic mutation detection is crucial for early disease diagnosis, prognosis assessment, and the implementation of precision medicine, as it enables the identification of key biomarkers that directly influence treatment decisions and patient outcomes. Random Forest classifier can help select critical mutations by prioritizing informative genetic mutations for target-recognition probe design. We develop an...

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