Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for sub-phenotyping acute respiratory distress syndrome (ARDS) patients using machine learning are described. An example system may obtain training data comprising ARDS patient records, determine a number of ARDS patient sub-phenotypes based on the ARDS patient records using latent profile analysis, and then execute an iterative process for determining an optimal ARDS classifier for patient sub-phenotyping. The system may select the optimal ARDS classifier from the optimal modes of the plurality of machine learning classifiers by comparing the performance metrics and deploy the optimal ARDS classifier for ARDS patient sub-phenotyping and providing personalized treatment based on the optimal ARDS classifier.