Title: Recognition of Medication Related Entities from Discharge Summaries Using Ensembles of Classifiers
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Title: Recognition of Medication Information from Discharge Summaries Using Ensembles of Classifiers
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متن کاملRecognizing Medication related Entities in Hospital Discharge Summaries using Support Vector Machine
Due to the lack of annotated data sets, there are few studies on machine learning based approaches to extract named entities (NEs) in clinical text. The 2009 i2b2 NLP challenge is a task to extract six types of medication related NEs, including medication names, dosage, mode, frequency, duration, and reason from hospital discharge summaries. Several machine learning based systems have been deve...
متن کاملRecognition of medication information from discharge summaries using ensembles of classifiers
BACKGROUND Extraction of clinical information such as medications or problems from clinical text is an important task of clinical natural language processing (NLP). Rule-based methods are often used in clinical NLP systems because they are easy to adapt and customize. Recently, supervised machine learning methods have proven to be effective in clinical NLP as well. However, combining different ...
متن کاملA cascade of classifiers for extracting medication information from discharge summaries
BACKGROUND Extracting medication information from clinical records has many potential applications, and recently published research, systems, and competitions reflect an interest therein. Much of the early extraction work involved rules and lexicons, but more recently machine learning has been applied to the task. METHODS We present a hybrid system consisting of two parts. The first part, fie...
متن کاملImprovement of Chemical Named Entity Recognition through Sentence-based Random Under-sampling and Classifier Combination
Chemical Named Entity Recognition (NER) is the basic step for consequent information extraction tasks such as named entity resolution, drug-drug interaction discovery, extraction of the names of the molecules and their properties. Improvement in the performance of such systems may affects the quality of the subsequent tasks. Chemical text from which data for named entity recognition is extracte...
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