Efficient Deep Learning-Based Automated Diagnosis from Echocardiography with Contrastive Self-Supervised Learning

Information Science, Computer Science, Artificial Intelligence, Medicine, Medical Imaging, Cardiovascular System,
deep learning   self-supervised learning   contrastive learning   echocardiography   automated diagnosis   left ventricular hypertrophy   aortic stenosis  

Breakthrough in Automated Echocardiogram Diagnosis via Deep Learning: A Comparative Study of Self-Supervised Learning Methods Research Background With the rapid development of artificial intelligence and machine learning technologies, their role in medical imaging diagnosis is becoming increasingly significant. In particular, Self-Supervised Learni...

Using Large Language Models to Assess Public Perceptions Around Glucagon-Like Peptide-1 Receptor Agonists on Social Media

Information Science, Computer Science, Artificial Intelligence, Medicine, Environmental and Public Health, Endocrinology, Cardiovascular System,
Obesity   Glucagon-like Peptide-1 Receptor Agonists   Social Media   Public Perception   Natural Language Processing  

In the global context, the prevalence of obesity is on the rise, bringing significant impacts to public health. Obesity is independently associated with the incidence and mortality of cardiovascular diseases, with an estimated economic burden exceeding $200 billion annually for healthcare systems. In recent years, glucagon-like peptide-1 (GLP-1) re...

Cell Type Mapping of Inflammatory Muscle Diseases Highlights Selective Myofiber Vulnerability in Inclusion Body Myositis

Information Science, Electronic Information, Computer Science, Artificial Intelligence,
Inflammatory Myofibers   Inclusion Body Myositis   Single-Nucleus RNA Sequencing   Spatial Transcriptomics   Myopathy   Cell Type   Gene Expression  

Characterization of Heterogeneity in Muscle Fiber Types and Selective Susceptibility in Inclusion Body Myositis With advancing age, the incidence of inflammatory myopathies gradually increases, among which inclusion body myositis (IBM) is the most common type, currently lacking effective treatment methods. Unlike other inflammatory myopathies, IBM ...

Investigating Useful Features for Overall Survival Prediction in Patients with Low-Grade Glioma Using Histology Slides

Information Science, Computer Science, Medicine, Medical Laboratory Science,
glioma   low-grade glioma   deep learning   histology   image processing   machine learning  

Useful Features for Overall Survival Prediction in Low-Grade Glioma Patients Academic Background Glioma is a type of neoplastic growth in the brain that usually poses a serious threat to the patients’ lives. In most cases, glioma eventually leads to the death of the patient. The analysis of glioma typically involves examining pathological slices of...

Improving the Segmentation of Pediatric Low-Grade Gliomas through Multitask Learning

Information Science, Artificial Intelligence, Medicine, Pediatrics, Medical Imaging, Oncology,
multitask learning   pediatric low-grade gliomas   MRI   tumor segmentation   deep learning  

Improved Segmentation of Pediatric Low-Grade Gliomas Through Multitask Learning Background Introduction The segmentation of pediatric brain tumors is a critical task in tumor volume analysis and artificial intelligence algorithms. However, this process is time-consuming and requires the expertise of neuroradiologists. Although significant research ...

Prediction of Glioma Grade Using Intratumoral and Peritumoral Radiomic Features from Multiparametric MRI Images

Information Science, Computer Science, Artificial Intelligence, Medicine, Medical Laboratory Science, Neurology, Medical Imaging, Oncology,
glioma grade   radiomics   intratumoral volumes   peritumoral volumes   multiparametric MRI   noninvasive  

“Prediction of Glioma Grades Based on Radiomic Features Inside and Outside Tumors Using Multiparametric MRI Images” Research Background Glioma is the most common primary brain tumor in the central nervous system, accounting for 80% of adult malignant brain tumors. In clinical practice, treatment decisions often require individualized adjustments ba...