Title : Transforming ovarian cancer care: AI innovations in early detection, overcoming challenges, enhancing patient safety, and promoting health equity
Abstract:
Background: Ovarian cancer remains a significant challenge in gynecological oncology due to its often late diagnosis and complex treatment pathways. Recent advancements in artificial intelligence (AI) offer promising avenues for early detection, improved patient safety, and equitable healthcare access.
Objectives: This review aims to explore how AI-driven innovations are transforming the landscape of ovarian cancer care. Key focus areas include early detection, overcoming clinical and technological challenges, enhancing patient safety, and promoting health equity.
Methods: A comprehensive review of current literature and case studies will be presented, highlighting AI applications in ovarian cancer detection and treatment. Ethical considerations and practical implementations of AI in clinical settings will also be discussed.
Results: Initial findings suggest that AI can significantly improve early detection rates and diagnostic accuracy. However, challenges such as algorithmic bias, data privacy, and integration into existing healthcare systems need to be addressed. Case studies demonstrate successful AI integration improving patient outcomes and safety.
Conclusions: AI innovations hold immense potential to revolutionize ovarian cancer care. By addressing existing challenges and promoting equitable healthcare access, AI can contribute to better patient outcomes and a more inclusive healthcare system.
Keywords: Ovarian cancer, AI innovations, early detection, patient safety, health equity
