Application of Artificial Intelligence in Healthcare: Trends, Challenges, and Ethical Implications.

Abstrak

Artificial Intelligence (AI) has seen rapid development and is increasingly implemented in various aspects of healthcare. This technology has the potential to improve diagnostic accuracy, enhance service efficiency, and support data-driven clinical decision-making. This study aims to systematically review the implementation of AI in the healthcare sector, focusing on its applications, challenges, and associated ethical and social implications. A systematic literature review was conducted using 11 peer-reviewed articles sourced from PubMed and major scientific journals. Articles were selected through predefined inclusion criteria and analyzed thematically to extract key themes. The results show that AI has been widely applied in medical image analysis, automated diagnosis, and clinical prediction, particularly through the use of deep learning models such as convolutional neural networks (CNN). These models demonstrated high performance in detecting diseases like cancer, diabetic retinopathy, and pulmonary conditions. However, implementation challenges remain, including limited interpretability of models, issues with data quality and algorithmic bias, and ethical concerns surrounding patient data privacy. In conclusion, AI holds significant promise for transforming healthcare, but its responsible and effective adoption requires robust regulatory frameworks, adequate infrastructure, and strong collaboration between AI systems and medical professionals.