Agentic AI in healthcare refers to AI systems that can autonomously make decisions, adapt to complex environments, and act in real-time, offering solutions for Proactive patient monitoring, predictive analytics, and optimized hospital operations.
Agentic AI systems can analyze Medical images, Lab results, and Patient histories to assist healthcare professionals in diagnosing diseases more accurately and quickly. For Example, AI algorithms have shown promise in detecting conditions such as cancer and cardiovascular diseases at early stages.
Build an agentic AI for the healthcare industry, you need to follow a structured approach, including defining clear goals, gathering relevant healthcare data, selecting appropriate algorithms, designing an agent architecture with perception, reasoning, and action capabilities, training the agent with reinforcement learning, and incorporating feedback mechanisms to continuously improve its decision-making in real-world healthcare