A Survey of Few-Shot Learning for Biomedical Time Series

arXiv:2405.02485v1 Announce Type: new
Abstract: Advancements in wearable sensor technologies and the digitization of medical records have contributed to the unprecedented ubiquity of biomedical time series data. Data-driven models have tremendous potential to assist clinical diagnosis and improve patient care by improving long-term monitoring capabilities, facilitating early disease detection and intervention, as well as promoting personalized healthcare delivery. However, accessing extensively labeled datasets to train data-hungry deep learning models encounters many barriers, such as long-tail distribution of rare diseases, cost …

abstract arxiv biomedical capabilities clinical contributed cs.ai cs.lg data data-driven detection diagnosis digitization disease few-shot few-shot learning improving long-term medical medical records monitoring patient patient care records sensor series survey technologies time series type wearable