Detecting anomalous anatomic regions in spatial transcriptomics with STANDS
Sign Up to like & getrecommendations! Published in 2024 at "Nature Communications"
DOI: 10.1038/s41467-024-52445-9
Abstract: Detection and Dissection of Anomalous Tissue Domains (DDATD) from multi-sample spatial transcriptomics (ST) data provides unprecedented opportunities to characterize anomalous tissue domains (ATDs), revealing both population-level and individual-specific pathogenic factors for understanding pathogenic heterogeneities behind… read more here.
Keywords: multi sample; spatial transcriptomics; tissue domains; detecting anomalous ... See more keywords
Detecting anomalous citation groups in journal networks
Sign Up to like & getrecommendations! Published in 2021 at "Scientific Reports"
DOI: 10.1038/s41598-021-93572-3
Abstract: The ever-increasing competitiveness in the academic publishing market incentivizes journal editors to pursue higher impact factors. This translates into journals becoming more selective, and, ultimately, into higher publication standards. However, the fixation on higher impact… read more here.
Keywords: impact factors; anomalous citation; detecting anomalous; citation groups ... See more keywords
V2AnomalyVec: Deep Discriminative Embeddings for Detecting Anomalous Activities in Surveillance Videos
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Computational Social Systems"
DOI: 10.1109/tcss.2021.3119957
Abstract: Understanding patterns in surveillance videos is always challenging due to the rapid movement of the crowd, occlusions, cluttered backgrounds, intraclass variations, and interclass similarities existing among normal and abnormal event classes. In the case of… read more here.
Keywords: anomalous events; detecting anomalous; deep discriminative; surveillance videos ... See more keywords