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Fig. 1 | Arthritis Research & Therapy

Fig. 1

From: Rule-based and machine learning algorithms identify patients with systemic sclerosis accurately in the electronic health record

Fig. 1

Development of algorithms to identify patients with systemic sclerosis (SSc) in the electronic health record (EHR). At least a 1-time count of the SSc ICD-9 code (710.1) or ICD-10-CM codes (M34*) was applied to the 3 million subjects in Vanderbilt’s Synthetic Derivative, which resulted in 1899 potential SSc cases. Of these 1899 potential SSc cases, 200 were randomly selected for a training set to develop and test algorithms with various combinations of the SSc ICD-9 and ICD-10-CM codes, keyword search for Raynaud’s phenomenon, and positive ANA (≥ 1:80). The highest performing algorithm was internally validated in a set of 100 subjects who were not part of the original training set

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