---
title: "Ainos expands Smell AI into breath analysis in National Taiwan University emergency medicine program"
type: "News"
locale: "en"
url: "https://longbridge.com/en/news/290048987.md"
description: "Ainos Inc. has launched a one-year research program with National Taiwan University starting July 1, 2026, to expand its Smell AI technology into breath-based diagnostics. The project aims to develop an AI electronic nose for the rapid triage of emergency patients with dyspnea by analyzing exhaled volatile organic compounds. Specifically, it seeks to train deep-learning models to differentiate between acute exacerbations of COPD and acute decompensated heart failure, potentially creating a proprietary database for future clinical use."
datetime: "2026-06-17T12:00:20.000Z"
locales:
  - [zh-CN](https://longbridge.com/zh-CN/news/290048987.md)
  - [en](https://longbridge.com/en/news/290048987.md)
  - [zh-HK](https://longbridge.com/zh-HK/news/290048987.md)
generator: "portal-rs"
---

# Ainos expands Smell AI into breath analysis in National Taiwan University emergency medicine program

-   Ainos launched a one-year research program with National Taiwan University starting July 1, 2026 to extend Smell AI into breath-based diagnostics. \* Project targets rapid triage of emergency patients with dyspnea using an AI electronic nose to analyze exhaled volatile organic compounds. \* Work aims to train and validate a deep-learning model to differentiate AECOPD from acute decompensated heart failure versus controls. \* Program could build a proprietary dyspnea breath-print database to support future clinical deployments, though the workflow remains research-stage. Disclaimer: This news brief was created by Public Technologies (PUBT) using generative artificial intelligence. While PUBT strives to provide accurate and timely information, this AI-generated content is for informational purposes only and should not be interpreted as financial, investment, or legal advice. Ainos Inc. published the original content used to generate this news brief via ACCESS Newswire (Ref. ID: 202606170800ACCESSWRNAPR\_\_\_\_\_1178463) on June 17, 2026, and is solely responsible for the information contained therein. © Copyright 2026 - Public Technologies (PUBT)

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> **Disclaimer: This article is for reference only and does not constitute any investment advice.**