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Register a new userDescription-based Label Attention Classifier for Explainable ICD-9 Classification
وصف الملصقات المستندة إلى وصف التصنيف لتصنيف ICD-9 للتفسير
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ترميز ICD-9 هي مهمة الفواتير السريرية ذات الصلة، حيث يتم تفاحص النصوص غير المنظمة مع معلومات حول تشخيص وعلاجات المريض مع رموز ICD-9 متعددة.الترميز الآلي ICD-9 هو حقل بحث نشط، حيث تمثل الهندسة النموذجية القائم على CNN و RNN النهج الحديثة من بين الفن.في هذا العمل، نقترح تصنيف اهتمام الملصقات القائمة على الوصف لتحسين الشريحة النموذجية عند التعامل مع النصوص الصاخبة مثل الملاحظات السريرية.
ICD-9 coding is a relevant clinical billing task, where unstructured texts with information about a patient's diagnosis and treatments are annotated with multiple ICD-9 codes. Automated ICD-9 coding is an active research field, where CNN- and RNN-based model architectures represent the state-of-the-art approaches. In this work, we propose a description-based label attention classifier to improve the model explainability when dealing with noisy texts like clinical notes.
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