Cesarean Section Classification Using Machine Learning With Feature Selection, Data Balancing, and Explainability
Disease rock cliff reservoir samples are naturally fewer than healthy samples which introduces bias in the training of machine learning (ML) models.Current study focuses in learning discriminating patterns between cesarean and non-cesarean phenomena based on a dataset consisting of 161 features of total 692 cesarean and 5465 non-cesarean samples wh