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Specialist physicians, specialist nurses and personnel in the intensive care unit (ICU) work to treat patients. Compared with other hospital units, ICUs are full-fledged and provide 24-h services. However, patients are admitted to this unit because of conditions such as severe trauma, organ failure or dysfunction and poisoning. The life expectancy of such patients is considerably low.

This study developed a reduced rule-based expert system to determine life expectancy. The purpose of this study is to determine the life expectancy of patients using ten variables. The rules were determined by evaluating 210 = 1,024 results. These rules were minimized using Boolean rules for simplification.

Conclusions were drawn by evaluating the minimized cases rather than evaluating 1,024 different cases. ICU patients were evaluated using this method, and the mean success rate was 63.75 per cent.

No rule-based expert system has been designed to determine the death risks of patients in the ICU.

Malaria is one of the most sinister life-threatening disease and generally transmitted by the bite of an Anopheles mosquito which was infected. These mosquitoes carry the Plasmodium parasite. Worldwide risk of malaria thread is very hard to deal, because of extreme temperature and climate changes which lead to uncontrolled changes in the mosquito population, as many deaths from malaria occur outside the healthcare system and other infections might be misdiagnosed as malaria unless a diagnostic test is done. The purpose of this study is creating a system which is early diagnosing malaria for settlements adequate healthcare units and non-immune travellers.

In this study’s system, the authors developed a new medical expert system (MES) process using the decreased rule base to detect malaria. The authors’ purpose was to successfully identify the illness by taking all symptoms of malaria into consideration in the MES (six basic signs, 64 different conditions). In the proposed MES process, in place of inspecting all the malaria-related signs, the authors used the decreased rule bases.

So as to take the lessen decreased bases, Boolean functions are used in a two-level simplification method. Using this method, decreased cases were evaluated by taking six symptoms of malaria into account instead of assessing 64 individual conditions.

The system can be used in diagnosis of asthma and chronic obstructive respiratory disease.

The system can be used in absence of adequate healthcare units. Thus, malaria can be diagnosed early.

The authors hope that the system they have developed will be useful for settlements in the absence of adequate healthcare units and non-immune travellers.