PURPOSE: To evaluate the value of pre-treatment MRI-based radiomics in patients with hepatocellular carcinoma (HCC) for the prediction of response to Yttrium 90 radiation segmentectomy.
Journal of the Formosan Medical Association = Taiwan yi zhi
Oct 25, 2024
PURPOSE: To compare deep learning (DL)-based and conventional reconstruction through subjective and objective analysis and ascertain whether DL-based reconstruction improves the quality and acquisition speed of clinical abdominal magnetic resonance i...
Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition
Oct 25, 2024
BACKGROUND: This study aimed to understand the collective impact of trace elements, vitamins, cholesterol, and prealbumin on patient outcomes in the intensive care unit (ICU) using an advanced artificial intelligence (AI) model for mortality predicti...
OBJECTIVES: This study aimed to evaluate critical care provider perspectives about diagnostic practices for rare and atypical infections and the potential for using artificial intelligence (AI) as a decision support system (DSS).
PURPOSE: To compare the quality of deep learning image reconstructed (DLIR) virtual monochromatic images (VMI) and material density (MD) iodine images from dual-energy computed tomography (DECT) for the evaluation of head and neck neoplasms with CT s...
BACKGROUND: Non-small cell lung cancer (NSCLC) is one of the leading causes of cancer mortality worldwide. Immune checkpoint inhibitors (ICIs) have emerged as a crucial treatment option for patients with advanced NSCLC. However, only a subset of pati...
BACKGROUND: Sensor-based remote health monitoring is increasingly used to detect adverse health in people living with dementia (PLwD) at home, aiming to prevent hospitalizations and reduce caregiver burden. However, home sensor data is often noisy, o...
Artificial Intelligence (AI) is poised to revolutionize healthcare by enhancing clinical practice, diagnostics, and patient care. Although AI offers potential benefits through data-driven insights and personalized treatments, challenges related to im...
PURPOSE: Although noninvasive tests can be used to predict liver fibrosis, their accuracy is limited for patients with severe obesity and nonalcoholic fatty liver disease (NAFLD). We developed machine learning (ML) models to predict significant liver...
Journal of the American Heart Association
Oct 25, 2024
BACKGROUND: Multicenter electronic health records can support quality improvement and comparative effectiveness research in stroke. However, limitations of electronic health record-based research include challenges in abstracting key clinical variabl...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.