Abstract

In this Internet era, people use more and more network data, and hospital diagnosis is even more important. The improvement of medical standards has brought about the rapid growth of medical data. How to analyze related symptoms from a large amount of data performing an analysis and accurately diagnosing its symptoms has become one of the difficult problems. This article is aimed at studying the role of medical huge amount of data and artificial intelligence in the diagnosis of knee osteoarthritis combined with cardiovascular and cerebrovascular diseases. To this end, this article proposes to improve data mining methods and proposes a comprehensive analysis of patient data in the field of artificial intelligence for intelligent diagnosis and treatment so that doctors can make accurate judgments about the symptoms of patients and designed related experiments to explore its specific effects. The experimental results in this article show that the improved data mining speed has increased by 17%, the data integrity has increased by 31%, and the proportion of valid data has also increased by 23%, which is very effective for clinical diagnosis.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.