Automated Classification of Computer-Based Medical Device Recalls: An Application of Natural Language Processing and Statistical Learning

Author

Alemzadeh, Homa ; Hoagland, Richie ; Kalbarczyk, Zbigniew ; Iyer, Ravishankar K.

Author_Institution

Coordinated Sci. Lab., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA

fYear

2014

fDate

27-29 May 2014

Firstpage

553

Lastpage

554

Abstract

This paper presents MedSafe, a framework for automated classification of computer-based medical device recalls. The data is collected from the U.S. Food and Drug Administration (FDA) recalls database. We combined techniques in natural language processing and statistical learning to automatically identify the computer-related recalls, by interpreting the natural language semantics of recall descriptions. We evaluated MedSafe on over 16K recall records submitted to the FDA between years 2007-2013.

Keywords

biomedical equipment; learning (artificial intelligence); natural language processing; pattern classification; statistical analysis; MedSafe; US FDA recall database; US Food and Drug Administration recall database; automated computer-based medical device recall classification; computer-related recalls; natural language processing; natural language semantics; statistical learning; Computers; Databases; Feature extraction; Measurement; Natural language processing; Statistical learning; US Government agencies; Computer-related Failures; FDA Recalls; Medical Devices; Natural Language Processing; Statistical Learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer-Based Medical Systems (CBMS), 2014 IEEE 27th International Symposium on

Conference_Location

New York, NY

Type

conf

DOI

10.1109/CBMS.2014.134

Filename

6881970