Abstract | Detection of aTTR-CM in a real-world heart failure population by NLP-guided automated data extraction from EHRs
The underdiagnosis as well as frequently delayed diagnosis of cardiac aTTR amyloidosis (aTTR-CM), a progressive and fatal cardiomyopathy, asks for improved screening.
In the study, the use of a systematic framework to diagnose aTTR-CM in a real-world heart failure population was explored.
It was found that detecting unique combinations of cardiac and non-cardiac phenotypes in Electronic Health Records through a Natural Language Processing-algorithm can facilitate earlier detection by raising the suspicion of aTTR-CM diagnosis.
Read the abstract linked above, as published by the American Heart Association (AHA).
In the study, the use of a systematic framework to diagnose aTTR-CM in a real-world heart failure population was explored.
It was found that detecting unique combinations of cardiac and non-cardiac phenotypes in Electronic Health Records through a Natural Language Processing-algorithm can facilitate earlier detection by raising the suspicion of aTTR-CM diagnosis.
Read the abstract linked above, as published by the American Heart Association (AHA).
