Latest AI and machine learning research in cardiovascular for healthcare professionals.
Chemotherapy-induced cardiotoxicity (CIC) is a leading cause of morbidity in cancer survivors, as conventional surveillance often detects cardiac dysfunction only after significant injury. This review moves beyond summarizing emerging technologies to focus on the end-to-end clinical pipeline-from sensor data to actionable decision-making-for creating a proactive "early-warning" system. We examine ...
PURPOSE: Nuclear emergency medical rescue is a critical component of the nuclear emergency response system, playing a vital role in safeguarding public life and health. To address the urgent need for rapid, wide-range radiation biodosimetry in nuclear emergency scenarios, this study utilized female C57BL/6J mice model to develop a machine learning (ML) framework for radiation-responsive biomarker ...
Nanomedicine offers powerful opportunities to overcome the pharmacokinetic and microenvironmental limitations of conventional chemotherapy, particular...
OBJECTIVE: To explore administrators' and clinicians' views on the factors that influence their use and adoption of a machine learning clinical decisi...
Neoadjuvant chemotherapy is a standard clinical practice for tumor downsizing in breast cancer, with [Formula: see text]F-FDG Positron Emission Tomogr...
Dendrobine exhibits notable anti-tumor activity against breast cancer (BRCA). In this study, we integrated network pharmacology, bioinformatics, and e...
BACKGROUND: Breast cancer is the most common malignancy in women and includes molecular subtypes with distinct clinical outcomes, such as luminal A an...
Contrast-enhanced CT is commonly used in the evaluation of hepatic metastatic lesions. This prospective study aimed to assess the capability of artifi...
BACKGROUND: Survival analysis in high-dimensional (HD) and multi-block (MB) settings, such as omic and multi-omic studies, poses major methodological ...
PURPOSE: Radiation necrosis (RN) is a challenging complication of cranial irradiation, often requiring corticosteroids for management. This study eval...
INTRODUCTION: Artificial intelligence (AI) in medical radiation science (MRS) is increasingly embedded in everyday clinical workflows. As AI systems a...
The assessment of tumor-infiltrating lymphocyte (TILs), together with gene expression signatures (GES), has the potential to guide personalized breast...
BACKGROUND: Overscanning is a common issue in CT planning, leading to unnecessary radiation exposure. PURPOSE: To develop a deep learning model to seg...
Advancements in drug delivery systems (DDSs) have revolutionized pharmaceutical development by enhancing therapeutic precision, minimizing off-target ...
PURPOSE: Detection of radiation-induced temporal lobe injury (RTLI) at the earliest radiologically detectable stage is important for timely interventi...
BACKGROUND: Artificial intelligence (AI) is considered to be a leading technology in radiation medical physics, which has the potential for improving ...
Glioblastoma is a highly aggressive primary brain tumor with near-universal recurrence despite maximal safe resection followed by standard chemoradiat...
BACKGROUND: Multidisciplinary tumor boards (MDTBs) play a central role in breast cancer management by integrating imaging findings with clinical and p...
Compact robotic systems offer new opportunities for spinal procedures outside the operating room, but their potential for small-scale interventions su...
Accurate prediction of Homologous Recombination Deficiency (HRD) is vital for personalized cancer therapy, yet genomic assays are often costly and com...