Researchers at the University of California, Los Angeles (UCLA), in collaboration with UC Berkeley, have developed a new type ...
Artificial intelligence (AI) is rapidly reshaping the landscape of leukemia diagnosis, offering new possibilities for earlier detection, more precise classification, and improved patient care, ...
A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN ...
Abstract: Sparse Bayesian learning (SBL) is an algorithm for high-dimensional data processing based on Bayesian statistical theory. Its goal is to improve the generalization ability and efficiency of ...
On-the-Fly Improving Segment Anything for Medical Image Segmentation Using Auxiliary Online Learning
Abstract: The current variants of the Segment Anything Model (SAM), which include the original SAM and Medical SAM, still lack the capability to produce sufficiently accurate segmentation for medical ...
This valuable work defines a "learning proteome" for a C. elegans gustatory associative learning paradigm. These results provide the field with a new set of genes to further explore their roles in ...
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