Department of Computer Engineering, Technology Faculty, Selçuk University, Selçuklu, Konya 42003, Turkey.
Department of Computer Technology and Computer Programming, Aksaray University, Aksaray, Turkey.
Comput Methods Programs Biomed. 2018 Apr;157:113-120. doi: 10.1016/j.cmpb.2018.01.020. Epub 2018 Feb 3.
A Medical Expert System (MES) was developed which uses Reduced Rule Base to diagnose cancer risk according to the symptoms in an individual. A total of 13 symptoms were used. With the new MES, the reduced rules are controlled instead of all possibilities (2= 8192 different possibilities occur). By controlling reduced rules, results are found more quickly. The method of two-level simplification of Boolean functions was used to obtain Reduced Rule Base. Thanks to the developed application with the number of dynamic inputs and outputs on different platforms, anyone can easily test their own cancer easily.
More accurate results were obtained considering all the possibilities related to cancer. Thirteen different risk factors were determined to determine the type of cancer. The truth table produced in our study has 13 inputs and 4 outputs. The Boolean Function Minimization method is used to obtain less situations by simplifying logical functions. Diagnosis of cancer quickly thanks to control of the simplified 4 output functions.
Diagnosis made with the 4 output values obtained using Reduced Rule Base was found to be quicker than diagnosis made by screening all 2= 8192 possibilities. With the improved MES, more probabilities were added to the process and more accurate diagnostic results were obtained. As a result of the simplification process in breast and renal cancer diagnosis 100% diagnosis speed gain, in cervical cancer and lung cancer diagnosis rate gain of 99% was obtained.
With Boolean function minimization, less number of rules is evaluated instead of evaluating a large number of rules. Reducing the number of rules allows the designed system to work more efficiently and to save time, and facilitates to transfer the rules to the designed Expert systems. Interfaces were developed in different software platforms to enable users to test the accuracy of the application. Any one is able to diagnose the cancer itself using determinative risk factors. Thereby likely to beat the cancer with early diagnosis.
开发了一种医学专家系统（MES），该系统使用简化规则库根据个体症状诊断癌症风险。共使用了 13 种症状。使用新的 MES，可以控制简化规则，而不是控制所有可能性（总共会有 2=8192 种不同的可能性）。通过控制简化规则，可以更快地找到结果。使用布尔函数的两级简化方法获得简化规则库。由于开发了具有不同平台上的动态输入和输出数量的应用程序，任何人都可以轻松地自行测试癌症风险。
考虑与癌症相关的所有可能性，可以获得更准确的结果。确定了 13 个不同的风险因素来确定癌症的类型。我们的研究生成的真值表有 13 个输入和 4 个输出。使用布尔函数最小化方法通过简化逻辑函数获得较少的情况。通过控制简化的 4 个输出函数，可以快速进行癌症诊断。
使用简化规则库获得的 4 个输出值进行诊断，比筛选所有 2=8192 种可能性进行诊断更快。使用改进的 MES，在过程中增加了更多的可能性，并获得了更准确的诊断结果。简化乳腺癌和肾癌诊断过程后，诊断速度提高了 100%，简化宫颈癌和肺癌诊断过程后，诊断速度提高了 99%。
通过布尔函数最小化，评估的规则数量减少，而不是评估大量规则。减少规则数量可以使设计的系统更高效地工作并节省时间，并方便将规则转移到设计的专家系统中。在不同的软件平台上开发了接口，以便用户测试应用程序的准确性。任何人都可以使用确定性风险因素自行诊断癌症。从而可以通过早期诊断战胜癌症。
