Heart failure & cardiomyopathies
INSIGHT Model: Explainable Artificial Intelligence for Real-World EHR-Based Screening of Transthyretin Amyloidosis Cardiomyopathy
Authors' conclusion
In an unselected HF population with 1% prevalence of suspected ATTR-CM, INSIGHT-CM identified patients among whom 1 in 5 fit the pattern for suspected ATTR-CM, offering meaningful opportunities to improve timely diagnosis and treatment.
Study context
- Population
- Unselected heart failure (HF) population, electronic health record data (April 2020-March 2023)patients with HF
- Participants
- 100,290 participants
Methodological detailsElectronic health record data, Natural language processing with Named Entity Recognition, Clinical ModernBERT, Local interpretable model-agnostic explanations
- Electronic health record data
- Natural language processing with Named Entity Recognition
- Clinical ModernBERT
- Local interpretable model-agnostic explanations
Main finding
As reported in the abstract
Identification of suspected ATTR-CM by INSIGHT-CM
| Group | Sensitivity | Specificity | Positive predictive value | Negative predictive value | Area under the receiver-operating characteristic curve |
|---|---|---|---|---|---|
| INSIGHT-CM | 77.5% (95% CI: 75.9%-82.8%) | 94.7% (95% CI: 94.4%-95.0%) | 19.9% (95% CI: 17.6%-22.36%) | 99.6% (95% CI: 99.5%-99.7%) | 92.4% (95% CI: 90.5%-94.3%) |
INSIGHT-CM
Sensitivity77.5% (95% CI: 75.9%-82.8%)
Specificity94.7% (95% CI: 94.4%-95.0%)
Positive predictive value19.9% (95% CI: 17.6%-22.36%)
Negative predictive value99.6% (95% CI: 99.5%-99.7%)
Area under the receiver-operating characteristic curve92.4% (95% CI: 90.5%-94.3%)
- Suspected ATTR-cardiomyopathy (ATTR-CM) n
- 1,108
- Prevalence
- 1.2%
Original publication
INSIGHT Model: Explainable Artificial Intelligence for Real-World EHR-Based Screening of Transthyretin Amyloidosis Cardiomyopathy. JACC Adv. Published 17 August 2026. doi:10.
Summarised from the published abstract; every number is checked against it