AIMC Topic: Cardiomegaly
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Logic-based machine learning predicts how escitalopram attenuates cardiomyocyte hypertrophy.
Proceedings of the National Academy of Sciences of the United States of America
Mar 4, 2025
Cardiomyocyte hypertrophy is a key clinical predictor of heart failure. High-throughput and AI-driven screens have the potential to identify drugs and downstream pathways that modulate cardiomyocyte hypertrophy. Here, we developed LogiRx, a logic-bas...
Segmentation-based cardiomegaly detection based on semi-supervised estimation of cardiothoracic ratio.
Scientific reports
Mar 8, 2024
The successful integration of neural networks in a clinical setting is still uncommon despite major successes achieved by artificial intelligence in other domains. This is mainly due to the black box characteristic of most optimized models and the un...
A deep-learning-based framework for identifying and localizing multiple abnormalities and assessing cardiomegaly in chest X-ray.
Nature communications
Feb 14, 2024
Accurate identification and localization of multiple abnormalities are crucial steps in the interpretation of chest X-rays (CXRs); however, the lack of a large CXR dataset with bounding boxes severely constrains accurate localization research based o...
A convolutional attention mapping deep neural network for classification and localization of cardiomegaly on chest X-rays.
Scientific reports
Apr 17, 2023
Building a reliable and precise model for disease classification and identifying abnormal sites can provide physicians assistance in their decision-making process. Deep learning based image analysis is a promising technique for enriching the decision...
Development of non-bias phenotypic drug screening for cardiomyocyte hypertrophy by image segmentation using deep learning.
Biochemical and biophysical research communications
Oct 1, 2022
The number of patients with heart failure and related deaths is rapidly increasing worldwide, making it a major problem. Cardiac hypertrophy is a crucial preliminary step in heart failure, but its treatment has not yet been fully successful. In this ...
An automated deep learning method and novel cardiac index to detect canine cardiomegaly from simple radiography.
Scientific reports
Aug 25, 2022
Since most of degenerative canine heart diseases accompany cardiomegaly, early detection of cardiac enlargement is main priority healthcare issue for dogs. In this study, we developed a new deep learning-based radiographic index quantifying canine he...
Diagnostic performance of artificial intelligence approved for adults for the interpretation of pediatric chest radiographs.
Scientific reports
Jun 17, 2022
Artificial intelligence (AI) applied to pediatric chest radiographs are yet scarce. This study evaluated whether AI-based software developed for adult chest radiographs can be used for pediatric chest radiographs. Pediatric patients (≤ 18 years old) ...
Contribution of phosphorus and PTH to the development of cardiac hypertrophy and fibrosis in an experimental model of chronic renal failure.
Nefrologia
Jan 3, 2022
BACKGROUND AND OBJECTIVE: Adequate serum phosphorus levels in patients with chronic kidney disease is essential for their clinical management. However, the control of hyperphosphatemia is difficult because is normally associated with increases in ser...
Evaluation of the feasibility of explainable computer-aided detection of cardiomegaly on chest radiographs using deep learning.
Scientific reports
Aug 19, 2021
We examined the feasibility of explainable computer-aided detection of cardiomegaly in routine clinical practice using segmentation-based methods. Overall, 793 retrospectively acquired posterior-anterior (PA) chest X-ray images (CXRs) of 793 patients...
Cardiothoracic ratio measurement using artificial intelligence: observer and method validation studies.
BMC medical imaging
Jun 7, 2021
BACKGROUND: Artificial Intelligence (AI) is a promising tool for cardiothoracic ratio (CTR) measurement that has been technically validated but not clinically evaluated on a large dataset. We observed and validated AI and manual methods for CTR measu...
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