Complaint and Diagnosis Extraction System Utilizing Rule-based Term Extraction System

نویسندگان

  • Koichi Takeuchi
  • Shozaburo Minamoto
  • Motoki Yamasaki
چکیده

In our laboratory, we have been developing a rule-based term extraction system in biomedical domain that contains hand-coded terms and domain specific suffixes, thus we construct a complaint and diagnosis extraction system utilizing the term extraction system. Since the rule-based system was constructed according to the annotated newspaper corpus [3], it must be inappropriate to direct application of the rule-based system to the target task, i.e., extraction of complaint and diagnoses expressions. To the other task that the rule-based system has expected, thus we propose a statistical learning method-based term extraction system using the rule-based term extraction system as major features.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Incorporating Unsupervised Features into CRF based Named Entity Recognition

We participated in the extraction of complaint and diagnosis Task and the normalization of complaint and diagnosis Task of MedNLP2 in NTCIR11. In the extraction Task, we use CRF based Named Entity Recognition method. Moreover, we incorporate unsupervised features learned from raw corpus into CRF. We show such unsupervised features improve system performance.

متن کامل

A Comparison of Rule-Based and Machine Learning Methods for Medical Information Extraction

This year's MedNLP (Morita and Kano, et al., 2013) has two tasks: de-identification and complaint and diagnosis. We tested both machine learning based methods and an ad-hoc rule-based method for the two tasks. For the de-identification task, the rule-based method achieved slightly higher results, while for the complaint and diagnosis task, the machine learning based method had much higher recal...

متن کامل

A Genetic Fuzzy Approach for Rule Extraction for Rule- Based Classification with Application to Medical Diagnosis

Rule extraction is an important task in knowledge discovery from imperfect training dataset in uncertain environments such as medical diagnosis. In a medical classification system for diagnosis, we cope with expensive or lack of expert knowledge in the design of the classifier. This paper presents an evolutionary fuzzy approach for tackling the problem of uncertainty in the process of rule extr...

متن کامل

Development of an Automatic Land Use Extraction System in Urban Areas using VHR Aerial Imagery and GIS Vector Data

Lack of detailed land use (LU) information and efficient data collection methods have made the modeling of urban systems difficult. This study aims to develop a novel hierarchical rule-based LU extraction framework using geographic vector and remotely sensed (RS) data, in order to extract detailed subzonal LU information, residential LU in this study. The LU extraction system is developed to ex...

متن کامل

A Framework for Semi-Automatic Development of Rule-based Information Extraction Applications

For the successful processing and handling of (large scale) document collections, effective information extraction methods are essential. This paper presents a framework for the semiautomatic development of rule-based information extraction applications based on the TEXTMARKER language utilizing machine learning methods. We describe the approach in detail and present the TEXTRULER system as an ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2013