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Fig. 1 | BMC Medical Informatics and Decision Making

Fig. 1

From: A computational clinical decision-supporting system to suggest effective anti-epileptic drugs for pediatric epilepsy patients based on deep learning models using patient’s medical history

Fig. 1

The data distribution of age, gender, and AED. a The distribution of patient age. b The distribution of patient gender. c The number of patients prescribed each AED. d The number of EEG interpretation reports corresponds to the ten most frequently prescribed AEDs. In (c) and (d), the top ten highly prescribed AEDs are shown and the target three AEDs of our drug suggestion system are colored in blue

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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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