Using deep autoencoders to identify abnormal brain structural patterns in neuropsychiatric disorders: A large‐scale multi‐sample study
Sign Up to like & getrecommendations! Published in 2019 at "Human Brain Mapping"
DOI: 10.1002/hbm.24423
Abstract: Machine learning is becoming an increasingly popular approach for investigating spatially distributed and subtle neuroanatomical alterations in brain‐based disorders. However, some machine learning models have been criticized for requiring a large number of cases in… read more here.
Keywords: using deep; autoencoders identify; model; deep autoencoders ... See more keywords
Natural Language Processing to Identify Abnormal Breast, Lung, and Cervical Cancer Screening Test Results from Unstructured Reports to Support Timely Follow-up
Sign Up to like & getrecommendations! Published in 2022 at "Studies in health technology and informatics"
DOI: 10.3233/shti220112
Abstract: Cancer screening and timely follow-up of abnormal results can reduce mortality. One barrier to follow-up is the failure to identify abnormal results. While EHRs have coded results for certain tests, cancer screening results are often… read more here.
Keywords: identify abnormal; language processing; cancer screening; timely follow ... See more keywords