The rapid evolution of neural networks and deep learning has revolutionized various fields, with clinical cardiology being no exception. As traditional methods in cardiology encounter limitations, the integration of advanced computational techniques ...
Cardiovascular diseases, particularly arrhythmias, remain a leading cause of mortality worldwide. Electrocardiogram (ECG) analysis plays a pivotal role in cardiovascular disease diagnosis. Although previous studies have focused on waveform analysis a...
Single-cell analysis (SCA) improves the detection of cancer, the immune system, and chronic diseases from complicated biological processes. SCA techniques generate high-dimensional, innovative, and complex data, making traditional analysis difficult ...
Blood-invasive fungal infections can cause the death of patients, while diagnosis of fungal infections is challenging. A high-speed microscopy detection system was constructed that included a microfluidic system, a microscope connected to a high-sp...
Understanding the mechanisms of protein-DNA binding is critical in comprehending gene regulation. Three-dimensional DNA structure, also described as DNA shape, plays a key role in these mechanisms. In this study, we present a deep learning-based meth...
BACKGROUND: Hip dysplasia is a condition where the acetabulum is too shallow to support the femoral head and is commonly considered a risk factor for hip osteoarthritis. The objective of this study was to develop a deep learning model to diagnose hip...
Contactless vital signs monitoring is a fast-advancing scientific field that aims to employ monitoring methods that do not necessitate the use of leads or physical attachments to the patient in order to overcome the shortcomings and limits of traditi...
INTRODUCTION: A growing number of studies on diagnostic imaging show superior efficiency and accuracy of computer-aided diagnostic systems compared to those of certified dentists. This methodological systematic review aimed to evaluate the different ...
With the rapid development of smart grids, society has become increasingly urgent to solve the problems of low energy utilization efficiency and high energy consumption. In this context, load identification has become a key element in formulating sci...
OBJECTIVES: Anti-HER2 targeted therapy significantly reduces risk of relapse in HER2 + breast cancer. New measures are needed for a precise risk stratification to guide (de-)escalation of anti-HER2 strategy.
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