AI Article Synopsis
- The study validated a neural network system designed to rank individuals based on the likelihood of having asthma, using responses from a community survey.
- The system successfully predicted the positive predictive value (PPV) for asthma based on set percentage thresholds, showing that a higher ranking correlated with a greater likelihood of clinical asthma diagnosis.
- As thresholds increased, the yield of clinically identified asthmatics decreased, but the system's predictions were generally accurate, helping healthcare providers plan for necessary resources in screening programs.
Article Abstract
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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| http://dx.doi.org/10.1016/j.annepidem.2004.03.006 | DOI Listing |
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