A Machine Learning Application to Predict Early Lung Involvement in Scleroderma: A Feasibility Evaluation

Abstract

Despite the notably small sample size, that could have prevented obtaining fully reliable data, the powerful tools available for ML can be useful for predicting early lung involvement in SSc patients. The use of predictors coming from spirometry and pH impedentiometry together might perform optimally for predicting early lung involvement in SSc.