Swarm intelligence-based medical diagnosis systems

Author(s):  
Punitha Stephan ◽  
Fadi Al-Turjman ◽  
Thompson Stephan
Author(s):  
Pandian Vasant

One of the most popular applications of artificial intelligence within the medical field is developing medical diagnosis systems. Because artificial-intelligence-based techniques are able to use pre-data and instant data flow for making predictions, it is an easy task to design intelligent systems that can give advice to people or perform diagnosis-based decision making. So, it has been an important research interest to design and develop intelligent systems, which are able to make diagnoses for medical purposes. In this sense, the objective of this chapter is to introduce a general medical diagnosis system that can be used for detecting diseases. In detail, the system employs artificial neural networks and swarm-intelligence-based techniques to form a general framework of intelligent diagnosis. The chapter briefly focuses on the infrastructure of the system and discusses its diagnosis potential.


Biotechnology ◽  
2019 ◽  
pp. 788-803
Author(s):  
Pandian Vasant

One of the most popular applications of artificial intelligence within the medical field is developing medical diagnosis systems. Because artificial-intelligence-based techniques are able to use pre-data and instant data flow for making predictions, it is an easy task to design intelligent systems that can give advice to people or perform diagnosis-based decision making. So, it has been an important research interest to design and develop intelligent systems, which are able to make diagnoses for medical purposes. In this sense, the objective of this chapter is to introduce a general medical diagnosis system that can be used for detecting diseases. In detail, the system employs artificial neural networks and swarm-intelligence-based techniques to form a general framework of intelligent diagnosis. The chapter briefly focuses on the infrastructure of the system and discusses its diagnosis potential.


1978 ◽  
Vol 17 (01) ◽  
pp. 28-35
Author(s):  
F. T. De Dombal

This paper discusses medical diagnosis from the clinicians point of view. The aim of the paper is to identify areas where computer science and information science may be of help to the practising clinician. Collection of data, analysis, and decision-making are discussed in turn. Finally, some specific recommendations are made for further joint research on the basis of experience around the world to date.


1978 ◽  
Vol 17 (01) ◽  
pp. 1-10 ◽  
Author(s):  
P. Tautu ◽  
G. Wagner

This paper is an analysis of the most important mathematical aspects of medical diagnosis: logical probability, rationality and decision theory, gambling models, pattern analysis, hazy and fuzzy subsets theory and, finally, the stochastic inquiry process.


JAMA ◽  
1966 ◽  
Vol 198 (3) ◽  
pp. 281-286 ◽  
Author(s):  
T. D. Sterling

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