TOWARDS AN AUTOMATIC DIAGNOSIS SYSTEM FOR ACUTE ABDOMINAL PAIN - Support Vector Machines for the Diagnosis of Diverticulitis and Non-specific Abdominal Pain

Author(s):  
Sadi Fuat Cankaya ◽  
Ibrahim Arda Cankaya ◽  
Tuncay Yigit ◽  
Arif Koyun

Artificial intelligence is widely enrolled in different types of real-world problems. In this context, developing diagnosis-based systems is one of the most popular research interests. Considering medical service purposes, using such systems has enabled doctors and other individuals taking roles in medical services to take instant, efficient expert support from computers. One cannot deny that intelligent systems are able to make diagnosis over any type of disease. That just depends on decision-making infrastructure of the formed intelligent diagnosis system. In the context of the explanations, this chapter introduces a diagnosis system formed by support vector machines (SVM) trained by vortex optimization algorithm (VOA). As a continuation of previously done works, the research considered here aims to diagnose diabetes. The chapter briefly gives information about details of the system and findings reached after using the developed system.


2012 ◽  
Vol 466-467 ◽  
pp. 1242-1245 ◽  
Author(s):  
Lin Zhang ◽  
Tao Liu ◽  
An Tang Zhang ◽  
Peng Xu ◽  
Ke Lian

Surface-to-air missile equipment is an advanced aerial defense weapon equipment of middle-high altitude intermediate range in our army, and this weapon equipment is also shouldering the significant task of antiaircraft defense of our country. Therefore, researching on its Fault Intelligent Diagnosis System has an important practical significance and military value on improving the weapon equipment’s renewing of fault and keeping the army’s battle effectiveness.


1983 ◽  
Vol 22 (01) ◽  
pp. 15-18 ◽  
Author(s):  
S. Brynitz ◽  
B. Bjerregaard ◽  
J. Holst-Christensen ◽  
P. Jess ◽  
Eeva Kalaja ◽  
...  

The reliability of medical record information is of fundamental importance to the certainty with which a diagnosis can be made. 40 patients were chosen at random and each was examined by four clinicians. The information and a tentative diagnosis were written on a special record form. The results were judged by means of the coefficient kappa. The clinicians disagreed more on symptoms than on diagnoses. The diagnoses made by an automatic diagnosis system showed lower precision and lower accuracy than the clinicians’ diagnoses. The results of the study might explain why computer assistance in diagnostics is of limited value.


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