Analysis, Visualization, and Predictive Insights of Cancer Diagnosis Data Using Tableau Public
Analysis, Visualization, and Predictive Insights of Cancer Diagnosis Data Using Tableau Public
Authors:
AjayRathod¹,PangaPrabhukiran²,K.Akshay³,Dr.G.Saritha⁴
¹²³Student, ⁴Assistant Professor, Department of Artificial Intelligence & Data Science
Methodist College of Engineering and Technology, Hyderabad, India
Email:ajveerrathod@gmail.com,prabhukiranpanga@gmail.com,akshaykinnera666@gmail.com,gsaritha@methodist.edu.in
Abstract:
Early cancer detection saves lives, but it depends on being able to interpret complex medical data reliably. This study explores that problem using a cancer diagnosis dataset — first by visualizing it in Tableau Public, then by running classification models to predict tumor type. Charts, heatmaps, and dashboards helped reveal how malignant and benign tumors differ structurally. Logistic Regression, Random Forest, and Decision Tree models were then tested to see how well those differences could be predicted automatically. Malignant tumors showed higher feature values and clustered more distinctly. The study is to finds that visualization and machine learning work better as a pair than either does on its own.
Keywords: Data Visualizations, Tableau Public, Machine Learning, Cancer Predictions, Exploratory Data Analysis, Healthcare Analytics Abstract: