Paper Title

INVESTIGATING THE ROLE OF DATA SCIENCE IN ENHANCING SURGICAL OUTCOMES: PREDICTIVE MODELS AND RISK ASSESSMENT TECHNIQUES

Keywords

data science
predictive models
machine learning
risk assessment
surgical outcomes
ensemble learning
neural networks
healthcare analytics
postoperative complications
personalized medicine.

Article Type

Research Article

Journal

Journal of Computer Engineering and Technology (JCET)

Publication Info

Volume: 5 | Issue: 1 | Pages: 52-71

Published On

May, 2022

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Abstract

This study investigates the role of data science in enhancing surgical outcomes through the application of predictive models and risk assessment techniques. By analyzing patient data from electronic health records, various machine learning models, including ensemble learning and neural networks, were developed and validated. The results demonstrate that ensemble learning models significantly outperform others in predicting postoperative complications, providing more accurate risk assessments. These findings suggest that integrating data-driven approaches into surgical practice can lead to more personalized and safer patient care. Future research should focus on improving model interpretability and validating their use in diverse clinical settings.