Implementing Machine Learning Algorithms in Java for Predictive Analytics in Healthcare

Authors: Abhishek Murikipudi

Country: United States

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Abstract: The focus of this article is to discuss how Java based ML models contribute to improving the current and or future predictive analysis within the health sector. Java makes data integration this easy through tools like DL4J, Weka and Apache Spark to support scalability and real-time predictive analysis. Open issues remain addressing the quality of input data, choice of the algorithm, and model complexity, while promising directions comprise the interpretability problem, data privacy, and resource allocation. These challenges call for mitigation measures which include hyperparameter tuning, usage of distributed computing and integration of cloud systems. The results show that Java seems more promising to shape the operation of healthcare and enhance the conditions of patients.

Keywords: Java-based ML models, Scalability, Hadoop, diagnosis, predictive model

Paper Id: 232050

Published On: 2025-01-22

Published In: Volume 13, Issue 1, January-February 2025

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