Health Technology/clinical-trials

Multicenter ML Study Opens: Predicting ABPA Exacerbation Risk to Transform Clinical Decision-Making in Allergic Bronchopulmonary Aspergillosis

247 Health News Editorial

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21 July 2026

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5 min read

·clinical-trials

A multicenter bidirectional cohort study (NCT07714863) is now recruiting to develop and externally validate a machine learning model predicting acute exacerbation risk in stable-phase ABPA patients. The study will compare nine ML algorithms and deploy SHAP-based interpretability tools and an interactive nomogram to support clinical decision-making. Results are anticipated to reshape risk stratification and treatment timing in this chronically relapsing condition.

Originally reported by ClinicalTrials.gov

References

  1. 1.Qianfoshan Hospital. (2025). Machine learning-based prediction of recurrence risk in allergic bronchopulmonary aspergillosis and its clinical decision-making value: A multicenter study with external validation (NCT07714863). ClinicalTrials.gov. https://clinicaltrials.gov/study/NCT07714863
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  3. 3.Agarwal, R., Muthu, V., Sehgal, I. S., Dhooria, S., Prasad, K. T., & Aggarwal, A. N. (2024). Allergic bronchopulmonary aspergillosis: Updates in the ISHAM-ABPA Working Group guidelines. Medical Mycology, 62(5), myae039. https://doi.org/10.1093/mmy/myae039
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  5. 5.Lundberg, S. M., & Lee, S. I. (2017). A unified approach to interpreting model predictions. Advances in Neural Information Processing Systems, 30, 4765–4774. https://doi.org/10.48550/arXiv.1705.07874
  6. 6.Patterson, T. F., Thompson, G. R., Denning, D. W., Fishman, J. A., Hadley, S., Herbrecht, R., Kontoyiannis, D. P., Marr, K. A., Morrison, V. A., Nguyen, M. H., Segal, B. H., Steinbach, W. J., Stevens, D. A., Walsh, T. J., Wingard, J. R., Young, J. A., & Bennett, J. E. (2016). Practice guidelines for the diagnosis and management of aspergillosis: 2016 update by the Infectious Diseases Society of America. Clinical Infectious Diseases, 63(4), e1–e60. https://doi.org/10.1093/cid/ciw326
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