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008 121227t2012 my da f m 000 0 eng d
020 _aTHE0001738(Local)
039 9 _a201905131217
_byusri
_c201212271159
_dhuda
_c201212271157
_dhuda
_y201212271157
_zhuda
040 _aUMP
090 _aQA76.66 .A33 2012 rs Bc.
100 0 _aAida Raihana Abd Wahab
245 1 0 _aHuman diseases diagnosis system (HDDS) /
_cAida Raihana Abd Wahab
260 _aKuantan, Pahang :
_bUMP,
_c2012
300 _axiv, 49 p. :
_bill. (some col.) ;
_c30 cm. +
_e1 CD- ROM
502 _aProject paper (Bachelor of Computer Science (Software Engineering)) -- Universiti Malaysia Pahang - 2012
504 _aBibliography : p. 49
520 3 _aAs we know that human disease diagnosis is a complicated process and requires high level of expertise. Any attempt of developing a web-based expert system dealing with human disease diagnosis has to overcome various difficulties. Detecting diseases at early stage can enable to overcome and treat them appropriately .Identifying the treatment accurately depends on the method that is used in diagnosing the diseases. Human Diseases Diagnosis Systems (HDDS) is an expert system that used to give earlier diagnosis of four major diseases, Chikungunya, Avian Influenza, H1N1 and Dengue. The idea to build the system by using expert systems is because expertise is not always available so that users can do their check up on the symptoms. So, by using this system can help them to give earlier diagnosis based on the questionnaires provided and lastly will generate the result of the disease. Besides that, user can get information of the diseases and be aware of the symptoms. This system is build by using PHP and MySQL as the database. Basic structure of rule based expert system are knowledge base, the database and the inference engine, explanation facilities and lastly is the user interface. The knowledge base for this system contains the knowledge useful for problem solving which is represented as a set of rules. The database includes a set of facts that used to match against the IF condition parts of rules that stored in the knowledge base. There are two types of inference which are forward and backward chaining. As for this system, it used forward chaining as its inference engine. This is because the reasoning is from facts to conclusion. Finally, it is hoped that this system can provide benefits to the users.
650 0 _aSystem design
650 0 _aSystem programming (Computer science)
999 _aVIRTUA40
_c3694
_d3700
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