Integrated therapeutic pharmacology system : intelligent prescription for medical practitioners using expert system / Siti Nur Saidah Sarpudin

Sarpudin, Siti Nur Saidah (2006) Integrated therapeutic pharmacology system : intelligent prescription for medical practitioners using expert system / Siti Nur Saidah Sarpudin. Degree thesis, Universiti Teknologi MARA.

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Abstract

The project is developing an Intelligent Prescription for Medical Practitioner Using Expert System. This system is use computer program or software which is develops by emulating human intelligence that could be used to assist the doctors in making decision without consulting the specialists directly and it produce the result based on current diseases, previous diseases and genetic disease. The main problem that occurred to doctors when they are making mistakes in prescribes the medicine and recommends dosage to their patients. So this system was developed for doctors and it may help them to give decision to prescribe the medicine for Diabetes (type one and two) and Migraine (stage one, two and three). This system also may help doctors to minimize error in choosing the medicine for patients. Other objective is to suggest doctors the suitable dosage for Diabetes (type two only) and Migraine (stage one, two and three). This system gives advantages for doctors and patients. For doctors, this system may help them to prescribe medicine in easier way, faster and more productive. While for patients, they would be safer when doctor make fewer mistakes on prescribing drugs. However, this software was not mean to replace the specialist or doctor, yet it was developed to assist general practitioner and specialist in diagnosing and predicting patient's condition from certain rules or "experience".

Item Type: Thesis (Degree)
Creators:
CreatorsEmail
Sarpudin, Siti Nur SaidahUNSPECIFIED
Subjects: Q Science > QA Mathematics > Instruments and machines > Electronic computers. Computer science
Q Science > QA Mathematics > Instruments and machines > Electronic computers. Computer science
Divisions: Faculty of Information Technology and Quantitative Sciences
Item ID: 975
Last Modified: 14 Nov 2018 07:53
Depositing User: Staf Pendigitalan 1
URI: http://ir.uitm.edu.my/id/eprint/975

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