LITL at CLEF eHealth2017: Automatic Classification of Death Reports

نویسندگان

  • Lydia-Mai Ho-Dac
  • Cécile Fabre
  • Anouk Birski
  • Imane Boudraa
  • Aline Bourriot
  • Manon Cassier
  • Léa Delvenne
  • Charline Garcia-Gonzalez
  • Eun-Bee Kang
  • Elisa Piccinini
  • Camille Rohrbacher
  • Aure Séguier
چکیده

This paper describes the participation of a group of students supervised by two teachers to the CLEF eHealth 2017 campaign, task 1. The task involves the classi cation of death certi cates in French and more precisely the labelling of each cause of death with the relevant ICD10 code. The system that performs the automatic coding is based on an information retrieval method using the Solr interface. Two runs were submitted according to whether the system distinguishes cases of multiple causes or not. The best performance was obtained with the system which distinguishes multiple causes, with a precision of 0.61 and a recall of 0.55.

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

LITL at CLEF eHealth2016: recognizing Entities in French Biomedical Documents

This paper describes the participation of master's students (LITL programme, university of Toulouse) and their teachers to the CLEF eHealth 2016 campaign. Two runs were submitted for task 2 (multilingual information extraction) which consisted in the recognition and categorization of medical entities in French biomedical documents. The system used consists of a CRF classi er based on a number o...

متن کامل

Baseline Results for the CLEF 2007 Medical Automatic Annotation Task

This paper provides baseline results for the medical automatic annotation task of CLEF 2007. Therefore, the algorithms initially used for the corresponding tasks in 2005 and 2006 are applied, using the same parameterization. Three classifiers based on global image features are used and combined within a nearest neighbor approach. In 2007, a hierarchical code is introduced to describe the image ...

متن کامل

A Lexicon Based Approach to Classification of ICD10 Codes. IMS Unipd at CLEF eHealth Task 1

In this paper, we describe the participation of the Information Management Systems (IMS) group at CLEF eHealth 2017 Task 1. In this task, participants are required to extract causes of death from death reports (in French and in English) and label them with the correct International Classification Diseases (ICD10) code. We tackled this task by focusing on the replicability and reproducibility of...

متن کامل

CLEF eHealth 2017 Multilingual Information Extraction task Overview: ICD10 Coding of Death Certificates in English and French

This paper reports on Task 1 of the 2017 CLEF eHealth evaluation lab which extended the previous information extraction tasks of ShARe/CLEF eHealth evaluation labs. The task continued with coding of death certificates, as introduced in CLEF eHealth 2016. This largescale classification task consisted of extracting causes of death as coded in the International Classification of Diseases, tenth re...

متن کامل

Clinical Information Extraction at the CLEF eHealth Evaluation lab 2016

This paper reports on Task 2 of the 2016 CLEF eHealth evaluation lab which extended the previous information extraction tasks of ShARe/CLEF eHealth evaluation labs. The task continued with named entity recognition and normalization in French narratives, as offered in CLEF eHealth 2015. Named entity recognition involved ten types of entities including disorders that were defined according to Sem...

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 2017