DDx Generator - Accuracy Studies
Several studies have shown, from even from Isabel’s earliest days, a high level of accuracy. In general, they show that in 95% of cases Isabel will include the correct final diagnosis in its list based on just the initial clinical features. The 4 studies listed below focus on accuracy and the last one looks at particularly difficult pediatric cases.
Accuracy of a Machine Learning Based Ddx Generator
563 cases of diagnostic error were collected over a period of 2 years from case reports, journals and detailed press articles. The cases covered 300 diagnoses and...
ISABEL: a web-based differential diagnostic aid for paediatrics: results from an initial performance evaluation
Setting: acute paediatric units in two teaching and two district general hospitals in the southeast of England. Materials: sets of summary clinical features from both stages, and the diagnoses expected for these features...
An international assessment of a web-based diagnostic tool in critically ill children
Improving diagnostic accuracy is essential. The extent of diagnostic uncertainty at patient admission is not well described in critically ill children. Therefore, we studied the extent that pediatric trainee diagnostic performance...
Performance of a web-based clinical diagnosis support system for internists
Clinical decision support systems can improve medical diagnosis and reduce diagnostic errors. Older systems, however, were cumbersome to use and had limited success in identifying the correct diagnosis...
“Asking Isabel” for diagnostic dilemmas in pediatrics: How does a web based diagnostic checklist perform
Diagnostic error is an important contributor to morbidity, mortality, and medical malpractice. The value of diagnostic decision support (DDS) tools in reducing diagnostic errors...
