Dip Nandi

Work place: American International University-Bangladesh, 408/1 (Old KA 66/1), Kuratoli, Khilkhet, Dhaka 1229, Bangladesh

E-mail: dip.nandi@aiub.edu


Research Interests: Distance education, E-learning, Online Education, Online learning


Prof. Dr. Dip Nandi received his PhD in Computer Science from RMIT University's School of Computer Science and Information Technology in Melbourne, Australia. He is an associate dean in the Department of Computer Science at American International University-Bangladesh. Online Learning, E-Learning, Online Education, Technology Enhanced Learning, Distance Education, Theory of e-Learning, ICT in Education are his research area. 

Author Articles
A Proposed Stacked Machine Learning Model to Predict the Survival of a Patient with Heart Failure

By Md. Raihan Mahmud Dip Nandi Md. Shamsur Rahim Christe Antora Chowdhury

DOI: https://doi.org/10.5815/ijisa.2024.03.03, Pub. Date: 8 Jun. 2024

Now a days heart failure is one of the most common chronic diseases that cause death. As it possesses high risk of death, it is important to predict patient’s survival and optimize treatment strategies. Machine learning techniques have come to light as useful tools for evaluating enormous quantities of patient data and deriving important patterns and insights in recent years. The purpose of the study is to investigate the feasibility of using the machine learning methods for predicting heart failure patient’s chances of survival. We have worked on a dataset with 2029 heart failure patients and the dataset comprises 13 features. To conduct this research, we suggested a model (Stacked machine learning model using scikit-learn using Decision Tree, Naive Bias, Random Forest, Linear Regression, SVM, XGBoost, ANN) using which we got better results than previously existed researches. We believe the suggested model will help advance our understanding of heart attack prediction.

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