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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/5397

Title: Developing a novel algorithm using machine learning for cancer prediction
Keywords: proteomic, genomic, ensemble learning, deep learing, miRN, biomarker
Researcher: Chaudhari Poonam Abhijeet
Guide(s): Dr. Agarwal Himanshu
Registration Date: 24-8-2013
Abstract: Cancer is a ghastly disease as it does not announce itself until it is at an advanced stage. There is no single test that can accurately diagnose cancer. Diagnosis of such a ruthless disease cannot be done only through clinical trials. It requires capability to deal with complex proteomic and genomic measurements. Thus, machine learning is frequently used in cancer diagnosis and detection. newline newlineMachine learning [2] is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to learn from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. Machine Learning is widely classified as Supervised Learning, Unsupervised Learning, Reinforcement Learning and Deep Learning. Lot of research has been done in supervised and unsupervised learning algorithms like Linear Regression, Decision Trees, Random Forest, Support Vector Machine, etc. newline newlineWe propose to define an algorithm which would make use of ensemble algorithms in deep learning to select a bio marker for lung cancer. This bio marker will help us in finding a specific gene expression from the miRNA sequence. Thus, predict the occurrence of the disease. newline newline newline
Language: English
Appears in Department:Faculty of Engineering

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