Analyzing And Extracting Information From Various Types of Medical Data

This article explores the vital role of medical data and big data in transforming healthcare practices. With the rapid growth in volume, diversity, speed, and value of these data, healthcare systems can utilize advanced and intelligent analytical techniques to significantly improve service quality, accurately identify fundamental issues, and predict future healthcare trends. The application of various data analysis methods, including exploratory data analysis, regression analysis, time series analysis, and deep learning, is crucial in uncovering hidden patterns and insights that enhance decision-making processes. These methods help increase the overall efficiency of treatment programs, optimize resource allocation, and improve patient outcomes. Additionally, integrating big data analytics supports personalized medicine and proactive healthcare management. This paper also discusses different techniques for data extraction and analysis, examines various types of regression analysis, and introduces software tools used for analyzing medical data and big data in healthcare environments.

کلیدواژه ها:

Medical data ، Big data in healthcare ، Data extraction and regression analysis