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Updated: Aug 20, 2026

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
Published on: July 22, 2025
Screening for asthma by population ranking: a validation study
Sybil Hirsch1, Timothy L Frank, Michelle Hazell
1General Practice Research Unit, North West Lung Research Centre, Wythenshawe Hospital, Manchester, M23 9LT, UK. sybil@miga.demon.co.uk
Purpose:
A neural network system was previously developed to rank a population in order of asthma probability based on responses to a postal questionnaire. Respondents ranked higher than a percentage point screening threshold are offered clinical review. The present study validates this system in a new population that had not been involved in system development.
Methods:
The system was used to rank respondents to a community survey and to predict positive predictive value (PPV) for percentage point thresholds between the top 1% and 10% of the ranking. Respondents in the top 10% were invited for clinical review. Review information and expert opinion was used to designate respondents as clinically "asthmatic" or "non-asthmatic." PPV prediction for each threshold was compared with clinical status of respondents.
Results:
As the threshold increased from 1% to 10%, the additional yield of clinical asthmatics decreased, indicating a ranking in asthma probability order (all 7 in the top 1% were clinical asthmatics compared with 91% of the top 5% and 83% of the top 10%). Percentages of clinical asthmatics were generally slightly higher than system PPV predictions.
Conclusions:
The system ranked the population in asthma probability order and estimated PPV conservatively, enabling health-care providers to predict resource implications of a screening program.
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