# Early Risk Prediction in Acute Aortic Syndrome on Clinical Data Using Machine Learning
## 2 Literature Review of AAS
### Literature Review Summary
\begin{table}
\begin{tabular}{p{56.9 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline
**Ref.** & **Variable** & **Sample Size** & **Preprocessing** & **Methods** & **Results** \\ \hline D. [PERSON] [22] & 17 & 1298 & Internal validation: 5-fold cross-validation & Logistic regression & AUC: 0.838 Sensitivity: 84\% Specificity: 91\% Accuracy: 0.94 \\ \hline R. [PERSON] [23] & 17 & 1340 & Continuous variables presented as means \(\pm\) standard deviation. Categorical variables presented as frequencies and percentages. Two-sided chi-square or [PERSON]’s exact test. & ADDRS, RIPP [PERSON] & AUC: 0.828 Sensitivity: 99.7\% Specificity: 53\% \\ \hline [PERSON]. [PERSON] [24] & 17 & 376 & Continuous variables presented as means \(\pm\) standard deviation; categorical variables presented as frequencies and percentages & ROC analysis used to determine the sensitivity and specificity of D-d at the cutoff value of 0.5 mg/L & AUC: 0.91 Sensitivity: 97.6\% Specificity: 63.2\% \\ \hline [PERSON]. [PERSON] [25] & 12 & 462 & Categorical data described as numbers and percentages. Continuous data displayed as mean with standard deviation (SD) or median with interquartile range & ADD-RS plus D-dimer & AUC: 0.91 Sensitivity: 93.1\% Specificity: 70.2\% \\ \hline F. [PERSON] [26] & 19 & 313 & Categorical variables reported as proportions plus 95\% confidence interval (CI). Mann–Whitney U test for non-parametric continuous variables. Kruskal-Wallis with post hoc Dunn’s multiple comparison test for independent samples. [PERSON]’s \(\chi\)2 test for categorical variables. & & AUC: 0.92 Sensitivity: 95.20\% Specificity: 46.60\% Specificity: 46.60\% \\ \hline D. [PERSON] [27] & 7 & 558 & Chi-square test used for categorical variables. Normality tests performed for continuous variables. & Multivariate logistic regression & AUC: 0.928 Sensitivity: 100\% Specificity: 67.8\% Specificity: 67.8\% \\ \hline F. [PERSON] [28] & 23 & 630 & Two-tailed Student’s \(t\)-test \(\chi\)2 test employed for categorical variables. Independent sample Mann–Whitney U test used for non-normally distributed data. & Logistic regression & AUC: 0.919 Sensitivity: 89.3\% Specificity: 80.6\% \\ \hline F. [PERSON] [29] & 12 & 3330 & Feature coefficient and heat maps & Multivariable logistic regression & AUC: 0.729 Sensitivity: 100\% Specificity: 43.1\% \\ \hline L. [PERSON] [30] & 5 & 569 & Internal validation: 20 repetitions of 10-fold cross-validation external validation & Multivariate logistic regression & AUC: 0.833 Sensitivity: 91\% Specificity: 87\% \\ \hline \end{tabular}
\end{table} 
Table 1: _Cont._comprehensive thesis addresses this limitation by incorporating a substantial total sample size of 148,707 cases with 42 clinical variables' data that will be explained more in the next section, which is about the data. This marks a significant transition into the realm of big data compared to earlier, smaller studies in the field of Acute Aortic Syndrome (AAS). Significantly, this extensive dataset also holds potential applicability for predicting various heart diseases beyond AAS.