INVESTIGATION AND THE ANALYSIS OF MEDICAL BIG DATA AND THE EMPLOYMENT OF ARTIFICIAL INTELLIGENCE FOR DISEASE PREDICTION
Authors: Aynur Jabiyeva Aynur Jabiyeva 
Published: January 2024

The development of technologies like big data, cloud services, Internet+, and artificial intelligence has greatly improved data communication services in the traditional pharmaceutical industry, driving the progress of the healthcare sector in our country. These advancements have facilitated healthcare system reforms, enhanced the quality and efficiency of medical services, and fostered technological innovation. In this context, our research focuses on the following areas and draws the following conclusions: In recent years, the pharmaceutical industry has leveraged technologies such as big data, cloud computing, Internet+, and artificial intelligence to enhance data transmission services. These advancements are considered crucial strategic resources for the pharmaceutical industry and ongoing healthcare system reforms in our country. Their goal is to improve the efficiency and quality of medical services, establish new models of healthcare delivery, and drive economic growth. Given this, our research aims to further explore these advancements. There is an increasing demand for an in-depth exploration of the utilization of logic in the fields of artificial intelligence and computer science. To address this need, the Manual of Logic in Artificial Intelligence and Logic Programming, along with its companion, the Manual of Logic in Computer Science, were developed. These resources combine comprehensive investigations and fundamental research to delve into various underlying topics across multiple disciplines. A foundational understanding of mathematical complexity is assumed as background knowledge, making the material of interest to logicians and mathematicians [1].
However, existing works primarily focus on core concepts and technologies, leaving out extensions, applications, and languages. The handbook aims to provide a comprehensive coverage of constraint programming, offering readers an accurate overview of the entire field and its potential. While each topic is presented in a survey-like manner, some details may be omitted in favor of broader coverage [2].Among various types of uncertainties, randomness and ambiguity are considered crucial and fundamental. The relationship between randomness and ambiguity is discussed, exploring uncertain states and their changes through measures like entropy and hyperentropy. The study investigates uncertainties in chaotic, fractal, and complex networks' evolutions and differentiations. A simple and effective method for simulating uncertainty through knowledge representation is proposed, providing a foundation for automating logical and visual thinking in the presence of uncertainty [4].
The appropriate timing for monitoring implementation remains unclear. Although there is room for improvement, if a data processing algorithm functions correctly, it can be employed separately from the original algorithm. However, there are limitations to its usage [5]
Keywords: Big Data, biomedicine, cluster, electronic health cards, healthcare.