Artificial intelligence through advances supports healthcare analysis while developing individual care platforms and operating system improvements. This research analyzes systematically the growth patterns and healthcare applications of AI while relying on Scopus database search results spanning from 2020 to 2025. A precise search method discovered main research publications which focused on diagnostic testing alongside telemedicine applications and data processing systems and AI ethical issues. A substantial growth in research productivity was demonstrated across the studied timeframe and diagnostics established itself as the primary research focus. Research demonstrates accelerating growth in AI applications across healthcare, which shows how important AI becomes for both diagnostic precision and patient success improvement. The study recognizes two major roadblocks that prevent AI adoption at scale: technical limitations about data privacy and the potential algorithm errors that threaten performance. These discoveries show how healthcare AI presents phenomenal transformation opportunities, yet developing ethical standards combined with secure data infrastructure becomes essential now. The research establishes essential knowledge about contemporary healthcare AI developments by outlining current uses and difficulties, which guide upcoming advancements in AI healthcare applications.