Feb. 29, 2024, 5:41 a.m. | Sunwoong Choi, Samuel Kim

cs.LG updates on arXiv.org arxiv.org

arXiv:2402.18046v1 Announce Type: new
Abstract: We present a novel data augmentation method to address the challenge of data scarcity in modeling longitudinal patterns in Electronic Health Records (EHR) of patients using natural language processing (NLP) algorithms. The proposed method generates augmented data by rearranging the orders of medical records within a visit where the order of elements are not obvious, if any. Applying the proposed method to the clopidogrel treatment failure detection task enabled up to 5.3% absolute improvement in …

abstract algorithms applications arxiv augmentation augmented data challenge cs.lg data detection ehr electronic electronic health records failure health language language processing modeling natural natural language natural language processing nlp novel orders patients patterns processing records treatment type

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