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A new study conducted by researchers at the Faculty of Electrical Engineering & Computer Science in Ostrava, Czech Republic, explores the use of fetal phonocardiography as an alternative to cardiotocography for monitoring fetal heart rate and uterine contractions. The study presents an automatic method for segmenting fetal heart sounds in a phonocardiographic signal, which is loaded with different types of disturbances. The researchers propose a hybrid classifier based on Transformer and eXtreme Gradient Boosting (XGBoost) to improve segmentation performance. The proposed method shows effective and promising performance, ranking first among all compared algorithms in precision, recall, F1, and accuracy scores. [Extracted from the article]

A study conducted by researchers at the School of Computer Science and Engineering in Vellore, India, has developed a novel approach for detecting and classifying myocardial infarction (MI) in echocardiogram frames using an enhanced CNN algorithm and an ECV-3D network. The proposed method aims to improve the accuracy and efficiency of MI diagnosis by leveraging advanced deep learning techniques. Through extensive experimentation, the researchers achieved an accuracy of 97.05% in the detection and classification of MI, indicating the potential of their method to significantly impact the accurate diagnosis of MI and improve patient outcomes. The proposed method is also suitable for real-time clinical applications. [Extracted from the article]

Researchers from the Department of Computer Science and Engineering at Shri Jagdishprasad Jhabarmal Tibrewala University in Rajasthan, India, have conducted a review of automated models for detecting cardiac arrhythmias. The researchers highlight the importance of early detection and prevention of cardiac disorders, as they are becoming increasingly prevalent due to factors such as stress, anxiety, and depression. The review evaluates the performance of the models based on various parameters and discusses their limitations and potential for improvement. The study emphasizes the use of electrocardiograms as a cost-effective method for diagnosing cardiac arrhythmias. [Extracted from the article]