The clinical associations with cardiomegaly in patients undergoing evaluation for pulmonary hypertension

Daines, Benjamin; Rao, Sanjana; Hosseini, Omid; Prieto, Sofia; Elmassry, Mohamed; Sethi, Pooja; Test, Victor; Nugent, Kenneth

doi:10.1080/20009666.2021.1982488

Cited by 2 publications

(1 citation statement)

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“…Cardiomegaly, a pathology frequently detected in chest x-rays (CXR), is a medical disorder in which a patient's heart enlarges temporarily or permanently depending on the situation. This enlargement is typically a clinical manifestation of another pathogenic condition, such as chamber dilation, ventricular hypertrophy, or pericardial effusion [Daines et al 2021], possibly resulting in heart failure, cardiac arrest, and sudden death [Cardenas et al 2020]. Routine chest radiographs showing cardiomegaly have significant clinical implications, since they help doctors decide whether additional investigation is necessary [Daines et al 2021].…”

Section: Introductionmentioning

confidence: 99%

Interpretable Deep Learning Model For Cardiomegaly Detection with Chest X-ray Images

Ribeiro,

Cardenas,

Krieger

et al. 2023

Anais Do XXIII Simpósio Brasileiro De Computação Aplicada À Saúde (SBCAS 2023)

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Cardiomegaly is a medical disorder characterized by an enlargement of the heart. Many works propose to automatically detect cardiomegaly through chest X-rays. However, most of them are based on deep learning models, known for their lack of interpretability. This work propose a deep learning model for the detection of cardiomegaly based on chest x-rays images and the qualitative assessment of three known local explainable methods, i.e., Grad-CAM, LIME and SHAP. Our model achieved Acc, Prec, Se, Spe, F1-score and AUROC of 91.8±0.7%, 74.0±2.7%, 87.0±5.5%, 92.9±1.2%, 79.8±1.9%, and 90.0±0.7%, respectively. Moreover, except for the SHAP method, our interpretable methods were able to pinpoint the expected location for cardiomegaly. However, Grad-CAM method showed faster computational time than LIME and SHAP.

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Section: Introductionmentioning

confidence: 99%