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The Reliable Intelligence and Medical Innovation Laboratory (RIMI Lab) is devoted to developing reliable artificial intelligence (RAI) theory to achieve balance, credibility, adaptation as well as interpretation, and developing RAI based models or methods for clinical problems, particular in cancer.

The fundamental theory is reliable AI. Three major methods are developed, they are: evidential learning, automated multi-objective learning and brain-inspired learning. Based on these methods, radiomics, delta radiomics, radiogenomics, and multi-omics are investigated.

Several clinical research are also conducted, including medical image processing, treatment outcome prediction, clinical diagnostic support, multimodal early screening, etc. In cancer research, we are working on treatment follow-up prediction, immunotherapy response prediction, neoadjuvant therapy response prediction, benign/malignancy diagnosis, early-stage screening, tumor segmentation, etc. We are also working on Alzheimer’s disease pathologies.