Cancer Prediction using RNA Sequencing and Machine Learning

Breast cancer is a type of tumour that develops in the breast tissues. It is the most common type of cancer found in women worldwide and is one of the leading causes of death in women. This article discusses Molecular subgroups are mostly used in research; they are not included in a patient's r...

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Veröffentlicht in:NeuroQuantology 2022-01, Vol.20 (10), p.1729
Hauptverfasser: ArunShalin, L V, I Sharath Chandra, Dhakne, Amol, Thiagarajan, R, Vaishali Rama Wadhe, Manikandan, T
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Sprache:eng
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Zusammenfassung:Breast cancer is a type of tumour that develops in the breast tissues. It is the most common type of cancer found in women worldwide and is one of the leading causes of death in women. This article discusses Molecular subgroups are mostly used in research; they are not included in a patient's report as well as are not utilized to guide treatment. However, the application of subtype has vastly expanded; identifying tumour subtypes can extensions by determining which genes are expressed in tumour samples. Many investigators have worked on breast cancer diagnosis and prognosis; each technology has a distinct accuracy rate, which varies based on the situation, tools, and sets of data used. Our primary goal is to compare various existing machine Learning techniques using RNA sequencing in order to determine the best method for supporting large datasets with high prediction precision. The primary goal of this review is breast cancer detection, and this study gives all needed details to analyse machine learning techniques in order to gain a solid understanding of pattern recognition
ISSN:1303-5150
DOI:10.14704/nq.2022.20.10.NQ55156