Android血液感染智能诊断模糊推理系统。使用

Gunjan Raghav, Harsh Khatter
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引用次数: 0

摘要

随着世界人口的日益增长,疾病/感染的机会也在增加。因此,这意味着需要一个自动化的解决方案,通过相关的患者数据可以发现疾病,并产生策展建议。从同一时间、同一地点患者的相同数据中了解所有可能的疾病是很困难的。对于这种疾病产生的每一种可能性,医生/专家都需要在全球范围内相互沟通。这一小时的需求是一个自动化的全球会诊加上疾病检测和管理系统解决方案,通过该解决方案,医生可以咨询位于其他地区的其他医生,从而能够找出共同的趋势问题及其解决方案。例如,巴西的一些问题,同样的情况也发生在印度,所以印度的医生会知道的。最终,印度的医生可以同意巴西的医生然后能够清除感染病史并进行准确的治疗。因此,我们提出的解决方案将帮助医生找到更准确的治疗未知/不明感染的方法。特别是日益出现的新疾病。本文提出的模型代表了一个自动化系统,该系统通过保存数据库中每一个未知疾病/感染的新条目来进行自我学习,并借助模糊逻辑和推理规则来识别已有的疾病/感染。因此,这可能是一种非常快速有效的方法,可以在全球范围内准确地跟踪疾病。该方法将使用模糊逻辑和模糊推理规则处理结构化数据。利用Android工具对所提出的系统进行仿真。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Curation Fuzzy Inference System System for Blood Infections in Android. using
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.
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