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Intelligent Curation Fuzzy Inference System System for Blood Infections in Android. using

机译:Android中血液感染的智能管理模糊推理系统。使用

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As the population of the world is increasing day by day so the chances of the number of diseases/infection arealso increasing.Hence it implies the need of an automated solution through which the relevant patient data could find out the disease and also result in the curation suggestion.It is difficult to know all the possible diseases from same data of patient at the same time and same location. For each and every probability of the disease coming out of it doctors/experts need to communicate with each other globally. The need o the hour is an automated global consulation plus disease detector and curation system solution by which doctors couldconsultthe other doctorssituated at other region and hence could be able to find out the common trending problems and their solutions. For Example some problem in Brazil & same status is happening in India, so the doctor in India would come to know about it. Eventually, the doctor in India canconsent to the doctor in Brazil then able to clear out the infection history and its accurate treatment. So our proposed solution would help doctors to find out the more accurate curation for the unknown / unidentified infection. Specially the new diseases which come in existence day by day. The paper presents the above mentioned proposed model which represents an automated system that could self learn by saving each new entry of previously unknown disease/ infection in the database and could identify the existing ones with the help of fuzzy logic and inference rules. So this could be the very fast and efficient way of following the diseases globally and accurately on the single ground. The proposed approach will work with the structured data using fuzzy logic with fuzzy inference rules. The simulation for the proposed system is done using the Android tool.
机译:随着世界人口的不断增加,疾病/感染数量的机会也在增加,因此这意味着需要一种自动化的解决方案,通过该解决方案,相关的患者数据可以发现疾病并进行治疗从患者的同一时间,同一地点的相同数据很难知道所有可能的疾病。对于每种可能出现的疾病,医生/专家都需要在全球范围内相互交流。每小时的需求是一种自动化的全球领事加疾病检测器和策展系统解决方案,医生可以通过该解决方案来咨询其他地区的其他医生,从而能够找出常见的趋势问题及其解决方案。例如,在巴西出现了一些问题,而在印度也发生了同样的状况,因此印度的医生会对此有所了解。最终,印度医生可以同意巴西医生的意见,从而能够清除感染史及其准确的治疗方法。因此,我们提出的解决方案将帮助医生找出更准确的治疗未知/未知感染的方法。特别是每天都存在的新疾病。本文提出了上述提议的模型,该模型代表了一种自动化系统,该系统可以通过将以前未知疾病/感染的每个新条目保存在数据库中来进行自学习,并可以借助模糊逻辑和推理规则来识别现有的系统。因此,这可能是一种快速而有效的方法,可以在全球范围内,准确地在单一领域跟踪疾病。所提出的方法将使用具有模糊推理规则的模糊逻辑处理结构化数据。拟议系统的仿真是使用Android工具完成的。

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