Cloud-edge AI system enhances rural clinical screening with LLM orchestration

Researchers have developed a novel cloud-edge system designed to improve multimodal clinical screening in rural areas with limited resources. This system utilizes lightweight, domain-specific models on edge devices to process raw medical data into structured outputs, which are then synthesized into clinical summaries by a cloud-based LLM. An LLM orchestrator dynamically selects diagnostic tools based on patient context, ensuring comprehensive modality coverage while minimizing irrelevant processing. The hybrid approach demonstrated high diagnostic tool recall and precision, matched or exceeded cloud-only baselines in clinical accuracy, and maintained consistent latency and reduced token costs across various network conditions. AI

IMPACT Enables advanced medical AI capabilities in resource-limited settings, improving diagnostic accuracy and efficiency.

RANK_REASON The cluster contains a research paper detailing a novel system architecture for AI-driven clinical screening. [lever_c_demoted from research: ic=1 ai=1.0]

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