• Akhtar Warsi
• Avanish Pratap Singh
• Kartikey Sharma
• Prerna Bhardwaj
• Arpit Sharma

The surging global healthcare costs have sparked a rise in interest for accurate and dependable methods to forecast medical expenses. Precise cost predictions can benefit healthcare providers, insurers, and policymakers in effectively allocating resources and enhancing the efficiency of healthcare services. To address this issue, this study delves into the use of machine learning classifiers for medical cost forecasting. Multiple models such as linear regression, polynomial classifier, random forest classifier, and decision tree classifier are examined. Moreover, feature importance analysis is conducted to identify the key variables that impact cost prediction. With a diverse dataset encompassing patient demographics, clinical data, and healthcare utilization variables, various machine learning classifiers are employed, including linear, polynomial, decision trees, and random forests, to construct predictive models. In addition, feature engineering methods are applied to extract valuable insights from the data, and hyperparameter tuning is utilized to optimize model performance. In conclusion, this research adds to the growing body of knowledge on healthcare and cost prediction by implementing machine learning classifiers. The developed models can assist healthcare stakeholders in making informed decisions regarding resource allocation, cost control, and patient care. The application of these predictive models has the potential to improve the overall effectiveness and sustainability of healthcare systems, ultimately resulting in better patient outcomes and cost-efficient delivery of healthcare services.

Medical cost prediction, Linear Regression, Random Forest classifier, polynomial classifier, Decision tree classifier, hyper parameters, optimization.

"Innovative Applications of Machine Learning Classifiers for Medical Cost and Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.a6-a15, April-2024, Available :http://www.jetir.org/papers/JETIR2404003.pdf

"Innovative Applications of Machine Learning Classifiers for Medical Cost and Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppa6-a15, April-2024, Available at : http://www.jetir.org/papers/JETIR2404003.pdf