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AI model aims to predict dangerous lung Flare-Ups in ABPA patients

NCT ID NCT07714863

Recruiting now Knowledge-focused Sponsor: Qianfoshan Hospital Source: ClinicalTrials.gov ↗

First seen Jul 20, 2026 · Last updated Jul 21, 2026 · Updated 1 time

Summary

This study develops a machine learning model to predict the risk of acute exacerbation within one year in patients with allergic bronchopulmonary aspergillosis (ABPA), a lung condition caused by allergic reactions to Aspergillus fungus. Researchers will analyze data from 200 stable-phase ABPA patients, using various clinical and lab features to build and validate 12 different models. The goal is to create a tool that helps doctors identify high-risk patients and make better treatment decisions.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

What this could lead to
If successful, this model could help doctors identify ABPA patients at high risk of flare-ups, enabling earlier and more personalized treatment.
What could go wrong
The model is based on data from 200 patients and may not generalize to all populations. Machine learning predictions are not always accurate in real-world settings.

This is an AI summary of the original study and may miss details. Read our disclaimer.

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Conditions

The condition(s) this trial relates to.

allergic bronchopulmonary aspergillosis

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

ABPA ACUTE EXACERBATION ALLERGIC BRONCHOPULMONARY ASPERGILLOSIS ALLERGIC BRONCHOPULMONARY ASPERGILLOSIS (ABPA) MACHINE LEARNING

Contacts and locations

Study contacts

  • Contact

    Phone: •••-•••-•••• Email: •••••@•••••

Locations

  • Department of Respiratory, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, #16766, Jingshi Road, Jinan City, Shandong Province, China

    RECRUITING

    Jinan, Shandong, 250014, China

    Contact Phone: •••-•••-•••• Email: •••••@•••••

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