Design Considerations of a Medical Expert System for Differential Diagnosis of Low Back Pain (ESLBP)

Author(s):  
Debarpita Santra ◽  
J. K. Mandal ◽  
S. K. Basu ◽  
Subrata Goswami
1947 ◽  
Vol 1 (5) ◽  
pp. 392-395 ◽  
Author(s):  
Maxwell Harbin

Author(s):  
Chiara Cricco ◽  
Antonella Daugenti ◽  
Domenico Angilecchia ◽  
Daniele Ceron

2015 ◽  
Vol 13 (3) ◽  
pp. 419-434
Author(s):  
H.O. Adeyemi ◽  
S.B. Adejuyigbe ◽  
S.O. Ismaila ◽  
A.F. Adekoya

Purpose – The purpose of this paper is to develop an expert system capable of assessing risk associated with manual lifting in construction tasks and proffer some first aid advices which are comparable with those obtainable from human experts. Design/methodology/approach – The expert system, musculoskeletal disorders – risk evaluation expert system (MSDs-REES), used Microsoft.Net C# programming language to write the algorithm of the fuzzy inference system with variables load, posture and frequency of lift as inputs and risk of low back pain as the output. The algorithm of the inference engine applied sets of rules to generate the output variable in crisp value. Findings – The result of validation, between the human experts’ calculated risk values and MSDs-REES-predicted risk values, indicated a correlation coefficient of 0.87. Between the predicted risk values generated using MSDs-REES and the existing package (MATLAB version 7.8), there was a strong positive relationship statistically with correlation coefficient of 0.97. Originality/value – The study provided a very simple expert system which has the ability to provide some medical-related injury prevention advice and first aid information for injury management, giving it a unique attribute over the existing applications.


2009 ◽  
Vol 0 (3) ◽  
pp. 8
Author(s):  
Nadezhda Aleksandrovna Shostak ◽  
N G Pravdyuk

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