AI Powered Multi-Agent Orchestration for Healthcare Diagnostics
作者 Infosys Ltd
Streamline healthcare diagnostics with AI-powered multiagent orchestration tools.
Solution Overview
Healthcare diagnostics is central to patient care, enabling early disease detection, accurate diagnosis, personalized treatments, and effective chronic condition management. Yet, diagnostic workflows today face systemic challenges: fragmented data sources, labor-intensive manual processes, cognitive overload for clinicians, and delays that compromise patient outcomes.
Infosys Multi-Agent Orchestration for Enhanced Healthcare Diagnostics leverages Agentic AI to transform this landscape. By orchestrating specialized AI agents across radiology, pathology, genomics, and clinical notes, the solution delivers unified, accurate, and timely diagnostic insights. Built on the Microsoft Azure platform, it takes advantage of Azure’s enterprise-grade security and compliance features, ensuring safe handling of healthcare data without requiring custom compliance configurations.
Key Capabilities
- Specialized
     Diagnostic Agents
 Radiology, Pathology, Genomics, and Clinical Notes agents independently analyze structured and unstructured data.
- Multi-Model
     Orchestration
 An Orchestrator Agent synthesizes multi-domain insights into a unified diagnostic recommendation.
- AI-Powered
     Data Processing
 Models are trained on pre-extracted features from diagnostic data (numerical and categorical representations), not raw images, ensuring efficiency, interpretability, and responsible AI usage.
- Clinical
     Decision Support
 Enable faster, more precise diagnosis while reducing manual effort for healthcare professionals.
- Secure
     by Design
 Leverages Microsoft Azure’s in-built security and compliance protocols to safeguard sensitive healthcare data.
Business Benefits
- Accelerate
     Diagnostics
 Reduce time to diagnosis with AI-driven multi-agent collaboration.
- Enhance
     Accuracy & Outcomes
 Improve diagnostic precision through integrated, cross-domain analysis.
- Reduce
     Clinician Burden
 Automate routine data analysis, freeing clinicians to focus on patient care.
- Enable
     Proactive Care
 Support early interventions and trial matching for better patient outcomes.