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Noora Health improves maternal care triage with LLM and rule engine

By PulseAugur Editorial · [1 sources] ·

Researchers at Noora Health have developed a new system to improve emergency triage for maternal and newborn care in India, utilizing a large language model (LLM) and a deterministic rule engine. This system classifies patient queries received via WhatsApp, distinguishing between emergencies and non-emergencies with enhanced accuracy and interpretability. The new approach has significantly improved recall and F1 scores, allowing clinicians to audit and update the system more efficiently, leading to faster correction loops and better patient care. AI

IMPACT Enhances AI's role in critical healthcare decisions, improving accuracy and auditability in emergency triage systems.

RANK_REASON The cluster contains a research paper detailing a novel system for healthcare triage using LLMs and rule engines. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Noora Health improves maternal care triage with LLM and rule engine

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The cluster contains a research paper detailing a novel system for healthcare triage using LLMs and rule engines. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Shobhit Jagga, Aman Dalmia, Niharika Priyadarshini, Neelima Devadas, Amrita K Prasen, Nikhil Nalin, Santhosh SJ, Sreeram Nurani Ramasubramanian, Muhammed Afeer K, Anubhav Arora ·

    Auditable Emergency Triage for Maternal and Newborn Care in India

    arXiv:2609.09356v1 Announce Type: new Abstract: At Noora Health, our nurses answer more than 50,000 medical queries per month on our WhatsApp-based service that provides caregivers with on-demand support. Their most time-critical task is emergency triage: deciding which queries n…

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