IMPLEMENTASI KECERDASAN BUATAN DALAM DIAGNOSTIK LABORATORIUM KLINIK: PELUANG DAN TANTANGAN - Muhammad Fachrul Hidayat (JURNAL KEPERAWATAN, 2026)
Background: The rapid development of artificial intelligence (AI) has significantly influenced clinical laboratory services, particularly in improving diagnostic accuracy, efficiency, and workflow automation. Objective: This review aims to analyze opportunities and challenges in implementing AI in clinical laboratory diagnostics. Methods: A narrative literature review was conducted using peer-reviewed articles published between 2021 and 2025, focusing on AI applications, ethical issues, and operational impacts in clinical laboratories. Results: AI demonstrates strong potential in image analysis, laboratory automation, predictive diagnostics, and decision support systems. However, challenges such as algorithmic bias, data validity, ethical concerns, and regulatory uncertainty remain critical barriers. Conclusion: AI can substantially enhance clinical laboratory performance if implemented cautiously through validated systems, ethical frameworks, and competent human oversight. Keywords: artificial intelligence; clinical laboratory; diagnostics; ethics