CARDIO-NET: A DEEP LEARNING -BASED CLINICAL DECISION SUPPORT SYSTEM FOR AUTOMATED CARDIOMEGALY DETECTION FROM CHEST X-RAY IMAGES
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Le résumé fourni par la source
Cardiovascular diseases are among the leading causes of mortality worldwide, necessitating early and accurate diagnosis [21]. Cardiomegaly is a significant indicator of underlying cardiac disorders and is commonly evaluated using chest X-ray imaging [6], [7]. However, manual interpretation of chest X-rays is time-consuming and requires expert radiologists. This paper presents Cardio-Net, a deep learning-based clinical decision support system for automated cardiomegaly detection using Deep Learning techniques [8], [13]. The proposed system employs a DenseNet-based model for classification [1], combined with image preprocessing using CLAHE to enhance image quality. Additionally, the system integrates cardiothoracic ratio (CTR) estimation [6], [7] and Grad-CAM visualization [3] for improved clinical interpretability. Experimental results demonstrate the effectiveness of the proposed system in assisting healthcare professionals in early diagnosis and decision-making.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- CARDIO-NET: A DEEP LEARNING -BASED CLINICAL DECISION SUPPORT SYSTEM FOR AUTOMATED CARDIOMEGALY DETECTION FROM CHEST X-RAY IMAGES
- Date Crossref
- 20/06/2026
- Éditeur
- Cerebration Science Publishing Co., Limited
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Indian Institute of Information Technology Department of Electronics and Communication Engineering (ECE) pays non établi dans la noticeUniversité ou école supérieure
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Visvesvaraya National Institute of Technology Department of Electronics and Communication Engineering (ECE) pays non établi dans la noticeUniversité ou école supérieure
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All India Institute of Medical Sciences Department of Radio-diagnosis pays non établi dans la noticeOrganisme public
Department of Electronics and Communication Engineering (ECE) — Indian Institute of Information Technology, Department of Electronics and Communication Engineering (ECE) — Visvesvaraya National Institute of Technology et Department of Radio-diagnosis — All India Institute of Medical Sciences.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.