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Prediction of significant congenital heart disease in infants and children using continuous wavelet transform and deep convolutional neural network with 12-lead electrocardiogram.
BMC pediatrics
Apr 24, 2025
BACKGROUND: Congenital heart disease (CHD) affects approximately 1% of newborns and is a leading cause of mortality in early childhood. Despite the importance of early detection, current screening methods, such as pulse oximetry and auscultation, hav...
Constructing machine learning-based risk prediction model for osteoarthritis in population aged 45 and above: NHANES 2011-2018.
Scientific reports
Apr 24, 2025
Osteoarthritis is a widespread chronic joint disease, becoming increasingly prevalent, particularly among individuals over the age of 45. This condition causes joint pain and dysfunction, significantly disrupting daily life. The objective of this stu...
Exploring hypoxia driven subtypes of pulmonary arterial hypertension through transcriptomics single cell sequencing and machine learning.
Scientific reports
Apr 24, 2025
Pulmonary arterial hypertension (PAH) is a progressive cardiovascular disease characterized by elevated pulmonary arterial pressure, leading to right heart failure and death. Despite advancements in diagnosis and treatment, it remains incurable, and ...
Leveraging TME features and multi-omics data with an advanced deep learning framework for improved Cancer survival prediction.
Scientific reports
Apr 24, 2025
Glioma, a malignant intracranial tumor with high invasiveness and heterogeneity, significantly impacts patient survival. This study integrates multi-omics data to improve prognostic prediction and identify therapeutic targets. Using single-cell data ...
Predicting outcomes following open abdominal aortic aneurysm repair using machine learning.
Scientific reports
Apr 24, 2025
Patients undergoing open surgical repair of abdominal aortic aneurysm (AAA) have a high risk of post-operative complications. However, there are no widely used tools to predict surgical risk in this population. We used machine learning (ML) technique...
Variational mode directed deep learning framework for breast lesion classification using ultrasound imaging.
Scientific reports
Apr 24, 2025
Breast cancer is the most prevalent cancer and the second cause of cancer related death among women in the United States. Accurate and early detection of breast cancer can reduce the number of mortalities. Recent works explore deep learning technique...
Identification of pivotal genes and regulatory networks associated with SAH based on multi-omics analysis and machine learning.
Scientific reports
Apr 24, 2025
Subarachnoid hemorrhage (SAH) is a disease with high mortality and morbidity, and its pathophysiology is complex but poorly understood. To investigate the potential therapeutic targets post-SAH, the SAH-related feature genes were screened by the comb...
A multi-filter deep transfer learning framework for image-based autism spectrum disorder detection.
Scientific reports
Apr 24, 2025
Autism Spectrum Disorder (ASD) affects approximately [Formula: see text] of the global population and is characterized by difficulties in social communication and repetitive or obsessive behaviors. Early detection of autism is crucial, as it allows t...
Decoding vital variables in predicting different phases of suicide among young adults with childhood sexual abuse: a machine learning approach.
Translational psychiatry
Apr 24, 2025
Young adults with childhood sexual abuse (CSA) are an especially vulnerable group to suicide. Suicide encompasses different phases, but for CSA survivors the salient factors precipitating suicide are rarely studied. In this study, from a progressive ...
Evaluating ChatGPT in Qualitative Thematic Analysis With Human Researchers in the Japanese Clinical Context and Its Cultural Interpretation Challenges: Comparative Qualitative Study.
Journal of medical Internet research
Apr 24, 2025
BACKGROUND: Qualitative research is crucial for understanding the values and beliefs underlying individual experiences, emotions, and behaviors, particularly in social sciences and health care. Traditionally reliant on manual analysis by experienced ...
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