Predicting blastocyst formation poses significant challenges in reproductive medicine and critically influences clinical decision-making regarding extended embryo culture. While previous research has primarily focused on determining whether an IVF cy...
Hip fractures among the elderly population continue to present significant risks and high mortality rates despite advancements in surgical procedures. In this study, we developed machine learning (ML) algorithms to estimate 30-day mortality risk post...
Due to the lack of validated universal seizure markers, population-level prediction methods often exhibit limited performance. This study proposes homologous microstate dynamic attributes as a generalized, subject-independent seizure marker. Homologo...
To propose a deep learning model and explore its performance in the auxiliary diagnosis of lung cancer associated with cystic airspaces (LCCA) in computed tomography (CT) images. This study is a retrospective analysis that incorporated a total of 342...
Hyperuricemia, the key pathological basis of gout, is increasingly prevalent worldwide. While lifestyle factors contribute, various medications also play a role. However, their specific risks and mechanisms remain inadequately studied. Disproportiona...
Social media has become an integral part of daily life, with platforms like Twitter serving as popular outlets for users to share information and express grievances. While social media offers numerous benefits, it can also be misused for cyberbullyin...
In this paper, three Double Machine Learning (DML) models are proposed to enhance the accuracy of breast cancer detection using machine learning techniques using breast cancer detection dataset. The DML models learn the primary features using machine...
This study aims to investigate the diagnostic value of integrating multi-parametric magnetic resonance imaging (mpMRI) radiomic features with tumor abnormal protein (TAP) and clinical characteristics for diagnosing prostate cancer. A cohort of 109 pa...
Automated segmentation of pediatric brain tumors (PBTs) can support precise diagnosis and treatment monitoring, but it is still poorly investigated in literature. This study proposes two different Deep Learning approaches for semantic segmentation of...
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that significantly impacts cognitive function, posing a major global health challenge. Despite its rising prevalence, particularly in low and middle-income countries, early diagnosi...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.