BACKGROUND AND OBJECTIVE: Bangladesh, a South Asian country, continues to face significant challenges in maternal health, as reflected by its high maternal mortality ratio (MMR). According to the 2022 Bangladesh Demographic and Health Survey (BDHS), ...
Machine learning (ML) offers great potential in healthcare, especially in the analysis of complex physiological signals like electroencephalography (EEG). EEG recordings hold valuable insights into neurological function and can aid in diagnosing vari...
BACKGROUND: Lung and Bronchus cancer is the most fatal type of cancer in the United States. According to the American Cancer Society, there were more than 127,000 deaths from lung cancer in 2023. Lung cancer care cost 23.8 billion dollars in 2020. In...
BACKGROUND: Residual cardiovascular risk persists in patients with hypercholesterolemia despite lipid-lowering therapy, underscoring the importance of inflammation in ASCVD development. This study evaluated the relationship between Systemic Inflammat...
PURPOSE: To apply quantitative imaging analysis for noninvasive classification of the most frequent subtypes of Non-Hodgkin Lymphoma (NHL) as a basis for a clinical imaging genomic model to support therapeutic monitoring and clinical decision making.
Recent studies have demonstrated that for various diseases, incorporating polygenic risk scores (PRSs) for other traits and diseases into the PRS-based risk prediction model may improve predictive performance - known as Multiple Polygenic Score (MPS)...
We evaluated the potential utility of imaging parameters derived by normalizing muscle signal intensity on T1-weighted lower leg MRIs in Charcot-Marie-Tooth disease type 1 A (CMT1A) patients, using a deep learning-based automated muscle segmentation ...
Knee abnormalities, such as meniscus tears and ligament injuries, are common in clinical practice and pose significant diagnostic challenges. While traditional imaging techniques-X-ray, Computed Tomography (CT) scan, and Magnetic Resonance Imaging (M...
Acute kidney injury is a common and severe complication following total hip arthroplasty, particularly in elderly or high-risk patients with chronic conditions, significantly increasing morbidity and mortality rates. Traditional prediction methods of...
This study explores the use of radiomic features extracted from preoperative T2-weighted MRI and CT images, combined with machine learning models, to predict the risk of vertebral refracture after percutaneous kyphoplasty (PKP) in postmenopausal wome...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.