DocumentCode
1426364
Title
Formal Design Methods for Reliable Computer-Aided Diagnosis: A Review
Author
Faust, O. ; Acharya, U.R. ; Tamura, T.
Author_Institution
Dept. of Electr. & Comput. Eng., Ngee Ann Polytech., Singapore, Singapore
Volume
5
fYear
2012
fDate
7/4/1905 12:00:00 AM
Firstpage
15
Lastpage
28
Abstract
Physiological signals, medical images, and biosystems can be used to access the health of a subject and they can support clinicians by improving the diagnosis for treatment purposes. Computer-aided diagnosis (CAD) in healthcare applications can help in automated decision making, visualization and extraction of hidden complex features to aid in the clinical diagnosis. These CAD systems focus on improving the quality of patient care with a minimum of fault due to device failures. In this paper, we argue that a formal and model driven design methodology can lead to systems which meet this requirement. Modeling is not new to CAD, but modeling for systems design is less explored. Therefore, we discuss selected systems design techniques and provide a more concrete design example on computer-aided diagnosis and automated decision making.
Keywords
data visualisation; decision making; feature extraction; formal specification; formal verification; health care; medical diagnostic computing; patient care; patient diagnosis; patient treatment; CAD system; automated decision making; biosystem; clinical diagnosis; clinician; computer-aided diagnosis reliability; device failure; diagnosis improvement; formal design method; healthcare application; hidden complex feature extraction; medical image; model driven design; patient care; physiological signal; subject health; system design; treatment purpose; visualization; Algorithms; Artificial neural networks; Computer aided diagnosis; Modeling; Reliability; Systems engineering and theory; Algorithms; artificial neural network (ANN); computer-aided diagnosis; formal methods; infrastructure; reliability; safety critical; systems engineering; Algorithms; Biomedical Engineering; Diagnosis, Computer-Assisted; Humans; Models, Statistical; Neural Networks (Computer);
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Reviews in
Publisher
ieee
ISSN
1937-3333
Type
jour
DOI
10.1109/RBME.2012.2184750
Filename
6135489
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