… The large number of clinical variables associated … artificial intelligence algorithm to identify
top clinical variable predictors and derive a risk stratification score system to help clinicians …

… superiority of artificial intelligence analysis, the novelty of our study is that we compared
various artificial intelligence techniques and used the ranking method of analytic variables. We …

… -learning model that combines a set of clinical variables and features in chest radiographs.
… artificial intelligence (AI) tool and a random forest analysis to identify critical clinical variables. …

… clinical application of the artificial neural network is that it could be used to afford greater
insights into the relationships between clinical variables … or computational analysis. Because the …

… papers have used artificial intelligence techniques and spectral analysis to more directly
analyze … In addition, clinical variables such as heart rate variability have been investigated to …

… recurrence and identifying the key variables. All the selected … stroke, and laboratory-based
variables were highly correlated with … to analyze the same dataset (clinical notes of 45 medical …

… of at least 1 to 4 for binary variables (absence/presence) and … 314 patients and the following
clinical parameters for the predictive … analysis on clinical data that modern machine learning …

… of variables and weights given to the input variables (referred to … , and deploying ML models
in the clinical setting. To our … natural intelligence (clinical experts) and artificial intelligence (…

… experimental limitations reduce their clinical utility. Deep learning … auto-encoding analyses
to train artificial neural networks to … machine learning was applied to 46 clinical variables from …

… , image feature analysis, and data classification via the use of tools such as artificial neural
… for each chest radiograph is somewhat variable, a simple subtraction technique could not …