Our aim is to propose a general and multilingual approach to render Diagnostic Terms into the standard framework provided by the ICD.

Our aim is to propose a general and multilingual approach to render Diagnostic Terms into the standard framework provided by the ICD.

A high performing pipeline for automated classification of reliable ICD-10 codes in the free medical text in cardiology that can be useful to decrease the ...

The column named Standard. Diagnostic Term shows the standard term describing each of the multiple ICD-10 codes manually assigned to the Original Text. 3.2.

The proposed decoder is based on the neural Belief Propagation algorithm and the Automorphism Group. By combining neural belief propagation with permutations ...

Sep 1, 2022 · This study presents a multimodal machine learning model to predict ICD-10 diagnostic codes. We developed separate machine learning models ...

Jul 6, 2023 · Chen et al. [15] proposed a deep neural network (DNN) model to predict the ICD-10 clinical modification code and achieved an F1-score of 0.715.

The result is an information model that allows to efficiently recommend codes to a new EHR based on their textual content. We explore an approach that proves to ...

Nov 22, 2023 · Interpretable deep learning to map diagnostic texts to icd-10 codes. International journal of medi- cal informatics, 129:49–59, 2019. URL ...

Feb 26, 2021 · We aimed to create a high performing pipeline for automated classification of reliable ICD-10 codes in the free medical text in cardiology.