A multicenter random forest model for effective prognosis prediction in collaborative clinical research network

ConclusionThe proposed random forest model exhibits ideal prediction capability using multicenter clinical data and overcomes the performance limitation arising from privacy guarantees. It can also provide feature importance ranking across institutions without pooling the data at a central site. This study offers a practical solution for building a prognosis prediction model in the collaborative clinical research network and solves practical issues in real-world applications of medical artificial intelligence.
Source: Artificial Intelligence in Medicine - Category: Bioinformatics Source Type: research