Agentic AI for Prostate Cancer: A Vision for Multimodal Clinical Intelligence

Area of Science:

• Oncology
• Medical Informatics
• Artificial Intelligence

Background:

• Artificial intelligence (AI) shows promise in prostate cancer diagnostics and treatment planning.
• The integration of AI into routine clinical decision-making for prostate cancer remains limited.
• A need exists for tools that can effectively synthesize diverse clinical data to support oncologists.

Purpose of the Study:

• To introduce and describe the concept of Agentic AI systems.
• To highlight the role of Agentic AI systems as an orchestration layer for various AI agents.
• To propose Agentic AI systems as a solution for enhancing clinical decision-making in prostate cancer care.

Main Methods:

• Development of Agentic AI systems.
• Integration of multiple AI agents within an orchestration layer.
• Focus on synthesizing diverse clinical information for decision support.

Main Results:

• Agentic AI systems are conceptualized as a method to bridge the gap between AI advancements and clinical practice.
• These systems are designed to process and synthesize varied data inputs.
• The proposed systems aim to provide effective support for clinicians' decision-making processes.

Conclusions:

• Agentic AI systems represent a novel approach to leveraging AI in clinical oncology.
• Effective synthesis of clinical information is crucial for improving AI's impact on patient care.
• Further development of Agentic AI systems is expected to enhance clinical decision-making in prostate cancer management.