Prediction on Patient Treatment Time Based on Machine Learning Approach

Authors

T. Suganya, Assistant Professor,
Department of Computer Science and engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India – 641042.

Ranjithkumar M, Elango R, K Hari Krishnan
UG Students, Department of Computer Science and engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India – 641042.

Abstract

Clinical support decision-production in medical care is now being impacted by expectations or proposals made by information driven machines. Various Artificial Intelligence (AI) applications have showed up in the most recent clinical writing, particularly for result forecast models, with results going from mortality and heart failure to intense. In this undertaking, sum up the best in class in related works covering information handling, derivation, and model assessment, with regards to result expectation models created utilizing information removed from electronic wellbeing records. Likewise examine impediments of conspicuous demonstrating suspicions and feature valuable open doors for future examination. The Patient treatment Time Prediction (PTTP) algorithm is very helpful in AI model time management analysis series to improve the predictions obtained. Computed Tomography (CT) severity score is forecasted using the AI models constructed. Virtual Machine setup is used for the graphical and visual observation of analysis results. Clinical Decision Support system is achieved using the PTTP analysis.