Textual extraction and classification for medical risk management: a new Risk Management Platform to manage undesired medical events

被引:0
作者
Zidi, Salah [1 ]
Julien, Thibaut [2 ]
Mjirda, Anis [3 ]
Maaloul, Fouad [2 ]
机构
[1] Qassim Univ, CBE, MIS Dept, POB 6633, Qasim 14452, Saudi Arabia
[2] SAS BIOMEDIQA, F-59650 Villeneuve Dascq, France
[3] Univ Valenciennes & Hainaut Cambrsis, LAMIH, Valenciennes, France
来源
2015 4TH IEEE INTERNATIONAL CONFERENCE ON ADVANCED LOGISTICS AND TRANSPORT (ICALT) | 2015年
关键词
Risk Management; Undesired events; Medical field; Textual extraction; Classifications; Machine learning; Support Vector Machines;
D O I
暂无
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
In this paper, we propose a semi-automatic system to deal with the undesired events that may happen in the medical field. Based on algorithms of textual extraction and classifications, it performs a preprocessing of undesired events' declarations. The proposed system is currently running on different hospitals and some medical institutions in France. Computational study were made on a real-case instances and experimentations shows good results for the proposed approaches.
引用
收藏
页码:298 / 302
页数:5
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