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Intelligent medical analysis platform
专利权人:
Université Hassan 1er
发明人:
BOUKENZE Basma,HAQIQ Abdelkrim,MOUSANNIF Hajar
申请号:
MA42165
公开号:
MA42165A1
申请日:
2018.03.12
申请国别(地区):
MA
年份:
2019
代理人:
摘要:
The invention relates to an intelligent platform for prediction data analysis, which can analyze all types of data regardless of its volume and any field, especially the health field. According to the risk factors of each disease, it analyzes and explores the data of patients so as to extract knowledge from them, which is useful for health workers to make decisions.Therefore, an intelligent diagnosis makes the detection more accurate,Provide permanent tracking, real-time monitoring and self-monitoring by predicting disease and disease development, predicting treatment, managing and even preventing disease development. The other sideReduce the cost of treatment and prepare patients in advance, rather than panicking them. The invention combines mobile technology and predictive analysis technology. The process of knowledge extraction in intelligent platform includes all steps of intelligent processingAMEC direct to the world advertising platform will use "cloud search" and "micro advertising" technology to provide you with accurate direct search services and professional advertising planning programs. The medical data analyzed are the data input by doctors and the data received by intelligent devices. This process is based on deep learning techniques.Data mining and machine learning Because many diseases are silent and develop without obvious symptoms, and diseases always cause pain, pain and treatment costs are generally high,The invention provides a new trend that will change various aspects of the medical sector by observing the health status of patients and even the future population.Cette invention concerne une smart plateforme d'analyse prédictive de données, capable d'analyser tous types de données quelque soit leur volume et dans n'importe quel secteur, notamment celui de la santé. Elle permet d'analyser et explorer les données des patients afin d'en extraire des connaissances, selon les facteurs de risque de chaque pathologie, les connaissances extraites sont
来源网站:
中国工程科技知识中心
来源网址:
http://www.ckcest.cn/home/

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