Predicting Likeliehood of Patients Survival After an Accident Using Statistical Regression

The purpose of this study is to develop a model employing regression techniques and deep learning to predict the likelihood of survival for patients hospitalized with illnesses typically observed in intensive care units (ICVs). Survival models are a sort of statistical technique that is commonly employed in clinical research. The objective of these models is to identify potential risk variables and forecast the risk of various clinical outcomes, such as the overall survival of patients with a variety of diseases The results show that our model can outperform the CPH prediction model when it comes to predicting the prognosis of CCV patients.