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Fig. 2 | BMC Medical Informatics and Decision Making

Fig. 2

From: Study on the semi-supervised learning-based patient similarity from heterogeneous electronic medical records

Fig. 2

Calculation of the feature similarity for the comorbidity condition. The example patients have comorbidity conditions \(\left\{ {K269, K293, K598, K621} \right\}\) and \(\left\{ {K269, K293, K598, K621} \right\}\) (in shadow), respectively. a The pre-built study corpus. K, K2, K26, and K269 and E, E1, E11, and E116 are the qualified ICD-10 code fragments from K269 and E116, respectively; b identification of the nearest common ancestor (NCA). K29 is the NCA for K295 and K293, K2 for K295 and K269, and K for the rest six pairs of ICD-10 code; c Calculation of the comorbidity condition similarity using information content

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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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