A Classification Process for Detection Lung Cancer at Early Stage using Machine Learning Techniques

In today’s world diabetes is the major health challenges in India. It is a group of a syndrome that results in too much sugar in the blood. It is a protracted condition that affects the way the body mechanizes the blood sugar. Prevention and prediction of diabetes mellitus is increasingly gaining interest in medical sciences. The aim is how to predict at an early stage of diabetes using different machine learning techniques. In this paper basically, we use well-known classification that are Decision tree, K-Nearest Neighbors, Support Vector Machine, and Random forest. These classification techniques used with Pima Indians diabetes dataset. Therefore, we predict diabetes at different stage and analyze the performance of different classification techniques. We Also proposed a conceptual model for the prediction of diabetes mellitus using different machine learning techniques. In this paper we also compare the accuracy of the different machine learning techniques to finding the diabetes mellitus at early stage.

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Improving the Performance of Lung Cancer Prediction Using Machine Learning Techniques on Big Data

International Journal of Computer Science and Mobile Computing ◽

10.47760/ijcsmc.2020.v09i10.008 ◽

2020 ◽

Vol 9 (10) ◽

pp. 64-72

Author(s):

Dr. M. Kasthuri ◽

M. Riyana Jency

Keyword(s):

Machine Learning ◽

Lung Cancer ◽

Big Data ◽

Machine Learning Techniques ◽

Cancer Prediction ◽

Learning Techniques

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Application of Machine Learning for Prediction of Lung Cancer using Omics Data

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.f3625.049620 ◽

2020 ◽

Vol 9 (6) ◽

pp. 230-236

Keyword(s):

Machine Learning ◽

Lung Cancer ◽

Data Mining ◽

Survival Analysis ◽

Early Stage ◽

Image Data ◽

Machine Learning Algorithms ◽

Machine Learning Techniques ◽

Data Sets ◽

Omics Data

Cancer is one of the deadly diseases across many countries. However, cancer can be cured, if detected at an early stage. Researchers are working on healthcare for early detection and prevention of cancer. Medical data has reached its utmost potential by providing researchers with huge data sets collected from all over the globe. In the present scenario, Machine Learning has been widely used in the area of cancer diagnosis and prognosis. Survival analysis may help in the prediction of the early onset of disease, relapse, re-occurrence of diseases and biomarker identification. Applications of machine learning and data mining methods in medical field are currently the most widespread in cancer detection and survival analysis. In this survey, different ways to detect and predict lung cancer using latest Machine learning algorithms combined with data mining has been analyzed. Comparative study of various machine learning techniques and technologies has been done over different types of data such as clinical data, omics data, image data etc.

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