Artificial Intelligence in Clinical Practice: Opportunities and Challenges

The integration of Artificial Intelligence (AI) into clinical practice represents a trans
formative shift in healthcare, offering unprecedented opportunities to enhance diagnostic accuracy,
personalize treatment, and optimize clinical workflows. This paper reviews the current applications,
opportunities, and challenges of AI in healthcare, with a focused case study on uterine fibroid detection
and management. We examine how machine learning, deep learning, and natural language processing
are revolutionizing medical imaging, predictive analytics, and clinical decision support. Despite
significant advancements, critical challenges persist, including data quality issues, algorithmic bias, lack
of explainability, and ethical concerns. The uterine fibroid case study illustrates both the potential and
limitations of clinical AI deployment. Successful integration requires interdisciplinary collaboration,
diverse datasets, explainable models, and robust regulatory frameworks. This paper provides a
comprehensive analysis for researchers, clinicians, and policymakers pursuing responsible AI
implementation in healthcare.