ANALYSIS OF HARDWARE AND SOFTWARE COMPLEXES FOR PRIMARY DIAGNOSTICS

Rustam Yaxshiboyev; Bahodir Muminov; Muzaffar Karimov

Авторы

Rustam Yaxshiboyev Tashkent State University оf Ecоnоmics
Bahodir Muminov Tashkent State University оf Ecоnоmics
Muzaffar Karimov Karshi Innovation University Of Education

Ключевые слова:

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

Аннотация

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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