The role of expert system shell induction in the analysis of phase and amplitude images obtained from nuclear cardiology

1991 ◽  
Vol 16 (2) ◽  
pp. 109-113
Author(s):  
A. S. Houston ◽  
A. Craig
Author(s):  
Vinothini Kasinathan ◽  
Aida Mustapha ◽  
Mohamad Firdaus Che Abdul Rani ◽  
Salama A. Mostafa

Chatterbots have been widely used as a tool for conversational booking assistance mainly for hotels such as the Expedia. This paper extends the use of chatterbot beyond booking by presenting the proof of concept of a chatterbot expert system called the VIZARD. The proposed VIZARD is developed using an expert system shell called verbot. The core of Vertbot 5 is the natural language processing (NLP) engine based on pattern matching. The core Verbot 5 engine is responsible for finding matches to a given user input string and firing the appropriate rule. The findings from the user acceptance test concluded that majority of the respondents agreed that the VIZARD expert system stands at an unbiased state while being more aligned on supporting the usefulness of the system.


1988 ◽  
Vol 23 (6) ◽  
pp. 35-38
Author(s):  
Victor Schneider

1988 ◽  
Vol 27 (01) ◽  
pp. 23-33 ◽  
Author(s):  
Fiorella de Rosis ◽  
G. Steve ◽  
C. Biagini ◽  
R. Maurizi-Enrici

SummaryThe decision process for diagnosis and treatment of Hodgkin’s disease at the Institute of Radiology of Rome has been modelled integrating the guidelines of a protocol with uncertainty aspects. Two models have been built, using a PROSPECTOR-like Expert System shell for microcomputers: the first of them treats the uncertainty by the inferential engine of the shell, the second is a probabilistic model. The decisions suggested in a group of simulated and real cases by a section of the two models have been compared with an “objective” final diagnosis; this analysis showed that, in some cases, the two models give different suggestions and that “approximations” of the shell’s inferential engine may induce wrong conclusions. A sensitivity analysis of the probabilistic model showed that the outputs are greatly influenced by variations of parameters, whose subjective estimation appears to be especially difficult. This experience gives the opportunity to consider the risks of building clinical decision models based on Expert System shells, if the assumptions and approximations hidden in the shell have not been previously analyzed in a careful and critical way.


Author(s):  
Devri Suherdi Chaniago

Penelitian ini dilakukan untuk mendiagnosa penyakit lambung yang lebih spesifik pada manusia yaitu grastitis, maag, kanker lambung, tumor lambung / polip lambung, dispesia, gerd, gastroparesis dan gastroenteritis,  dengan adanya gejala yang lebih spesifik maka persentase kemungkinan terjangkitnya penyakit lambung akan lebih besar. Sistem pakar untuk mendiagnosa penyakit lambung dengan menggunakan metode Fuzzy Mamdani dapat membantu meminimalisir peran dokter penyakit dalam sehingga pasien dapat lebih dini mendeteksi jenis penyakit lambung apa yang dideritanya. Sistem pakar berbasis web memungkinkan adanya peranan bidang informatika dalam bidang kesehatan dan dapat disimpan dalam file database yang besar sehingga lebih efisien, tepat sasaran dan mengikuti perkembangan dunia kedokteran. Dengan adanya gejala-gejala penyakit pecernaan yang dideteksi maka akan dapat didiagnosa jenis penyakit lambung apa yang di derita oleh pasien dengan hasil penelitian dapat mendeteksi jenis penyakit lambung, gejala-gejala dan solusi pengobatannya. This research was conducted to diagnose gastric diseases that are more specific to humans, namely grastitis, ulcers, gastric cancer, gastric tumors / gastric polyps, dyspesia, gerd, gastroparesis and gastroenteritis. With more specific symptoms, the percentage of gastric disease will be greater. An expert system for diagnosing gastric disease using the Fuzzy Mamdani method can help minimize the role of internal medicine doctors so that patients can detect what type of gastric disease they have early. The web-based expert system allows the role of informatics in the health sector and can be stored in a large database file so that it is more efficient, on target and follows developments in the medical world. With the detected gastrointestinal symptoms, the patient will be able to diagnose what type of gastric disease suffered by the patient with the results of the research being able to detect the type of gastric disease, its symptoms and treatment solutions.


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