ANALYSIS OF HARDWARE AND SOFTWARE COMPLEXES FOR PRIMARY DIAGNOSTICS

Authors

  • Yakhshiboyev Rustam Erkinboy o’g’li Tashkent State University оf Ecоnоmics
  • Mo’minov Bahodir Boltayevich Tashkent State University оf Ecоnоmics
  • Karimov Muzaffar Maxamatxonovich Karshi Innovation University Of Education

Keywords:

analysis, software and hardware complex, diagnostics, primary diagnostics, artificial intelligence, machine learning

Abstract

This article explores hardware and software complexes for primary diagnosis in the context of Uzbekistan's Presidential Decree No. PP - 4996 dated February 17, 2021, titled "Measures to Create Conditions for the Accelerated Implementation of Artificial Intelligence Technologies," and in alignment with the "Digital Uzbekistan 2030" strategy. An analysis of hardware and software  complexes for primary diagnosis of gastroenterological diseases is conducted based on joint scientific research with gastroenterology specialists at the Tashkent Medical Academy.

Technical specifications, cost, manufacturers, and the diagnostic process are examined. The analysis of hardware and software complexes for primary diagnosis in gastroenterology is divided into two parts: classical diagnostic tools and modern diagnostic instruments.

A comparison is made between the technical specifications, cost, manufacturers, and diagnostic processes of classical diagnostic tools and modern diagnostic instruments for gastroenterological diseases.

In the final part of the article, a new hardware and software complex called "Saliva" is introduced. This complex operates based on modern artificial intelligence technology, specifically utilizing deep learning algorithms. The Random Forest deep learning algorithm was adapted to the envisioned "Saliva" hardware and software complex.

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Published

2023-10-09

How to Cite

Yaxshiboyev, R., Muminov, B., & Karimov, M. (2023). ANALYSIS OF HARDWARE AND SOFTWARE COMPLEXES FOR PRIMARY DIAGNOSTICS. DIGITAL TRANSFORMATION AND ARTIFICIAL INTELLIGENCE, 1(3), 15–20. Retrieved from https://dtai.tsue.uz/index.php/dtai/article/view/v1i33