ANALYSIS OF CHALLENGES AND POSSIBILITIES OF USING ARTIFICIAL INTELLIGENCE IN MEDICAL DIAGNOSTICS

Area of Science:

• Scientific research
• Healthcare technology
• Artificial Intelligence

Background:

• Analysis of AI types and applications in healthcare.
• Documentation of AI implementation challenges.
• Assessment of AI's impact on healthcare efficiency.

Purpose of the Study:

• To analyze the geographical distribution of AI in healthcare.
• To identify challenges and opportunities for AI in healthcare.
• To evaluate the outcomes of AI applications in medicine.

Main Methods:

• Systematic review of 24 studies (2019-2024).
• Searches conducted in IEEE Xplore, PubMed, and Google Scholar.
• Utilized MeSH keywords with specific inclusion/exclusion criteria.

Main Results:

• AI, including deep learning and machine learning, is widely applied, especially in precision medicine and diagnostics.
• Key challenges include data shortages, algorithmic bias, and ethical/regulatory issues.
• Trends show multi-modal data integration, increased automation, and global standard convergence.

Conclusions:

• AI enhances medical diagnostic accuracy, speed, and personalization.
• Overcoming implementation barriers is essential for widespread AI use in healthcare.
• AI offers significant opportunities to transform healthcare delivery and efficiency.