Automatic ICD Code Assignment to Medical Text with Semantic Relational Tuples
نویسندگان
چکیده
Mining the Electronic Medical Record (EMR henceforth) is growing in popularity but still lacks good methods for better understanding the text in EMR. One important task is assigning proper International Classification of Diseases (ICD henceforth, which is the code schema for EMR) code based on the narrative text of EMR document. For the task, we propose an automatic feature extraction method by means of capturing semantic relational tuples. We proved the semantic relational tuple is able to capture information at semantic level and it contribute to ICD-9 classification task in two aspects, negation identification and feature generation.
منابع مشابه
Automatic Code Assignment to Medical Text
Code assignment is important for handling large amounts of electronic medical data in the modern hospital. However, only expert annotators with extensive training can assign codes. We present a system for the assignment of ICD-9-CM clinical codes to free text radiology reports. Our system assigns a code configuration, predicting one or more codes for each document. We combine three coding syste...
متن کاملA hierarchical method to automatically encode Chinese diagnoses through semantic similarity estimation
BACKGROUND The accumulation of medical documents in China has rapidly increased in the past years. We focus on developing a method that automatically performs ICD-10 code assignment to Chinese diagnoses from the electronic medical records to support the medical coding process in Chinese hospitals. METHODS We propose two encoding methods: one that directly determines the desired code (flat met...
متن کاملExtracting Semantic Networks from Text Via Relational Clustering
Extracting knowledge from text has long been a goal of AI. Initial approaches were purely logical and brittle. More recently, the availability of large quantities of text on the Web has led to the development of machine learning approaches. However, to date these have mainly extracted ground facts, as opposed to general knowledge. Other learning approaches can extract logical forms, but require...
متن کاملEnhancing Automatic ICD-9-CM Code Assignment for Medical Texts with PubMed
Assigning a standard ICD-9-CM code to disease symptoms in medical texts is an important task in the medical domain. Automating this process could greatly reduce the costs. However, the effectiveness of an automatic ICD-9-CM code classifier faces a serious problem, which can be triggered by unbalanced training data. Frequent diseases often have more training data, which helps its classification ...
متن کاملThree Approaches to Automatic Assignment of ICD-9-CM Codes to Radiology Reports
We describe and evaluate three systems for automatically predicting the ICD-9-CM codes of radiology reports from short excerpts of text. The first system benefits from an open source search engine, Lucene, and takes advantage of the relevance of reports to one another based on individual words. The second uses BoosTexter, a boosting algorithm based on n-grams (sequences of consecutive words) an...
متن کامل