OBJECTIVE: Little information is available about deep learning methods used in ultrasound images of salivary gland tumors. We aimed to compare the accuracy of the ultrasound-trained model to computed tomography or magnetic resonance imaging trained m...
Journal of magnetic resonance imaging : JMRI
May 23, 2023
BACKGROUND: The delineation of brain arteriovenous malformations (bAVMs) is crucial for subsequent treatment planning. Manual segmentation is time-consuming and labor-intensive. Applying deep learning to automatically detect and segment bAVM might he...
The international journal of medical robotics + computer assisted surgery : MRCAS
May 23, 2023
BACKGROUND: Thoracoscopic-assisted and robot-assisted Mckeown esophagectomy are currently two common surgical methods, but there is no clear statement on the advantages and disadvantages of the two.
Background There is considerable interest in the potential use of artificial intelligence (AI) systems in mammographic screening. However, it is essential to critically evaluate the performance of AI before it can become a modality used for independe...
OBJECTIVES: In multiple myeloma and its precursor stages, plasma cell infiltration (PCI) and cytogenetic aberrations are important for staging, risk stratification, and response assessment. However, invasive bone marrow (BM) biopsies cannot be perfor...
BACKGROUND: Analgesia after robot assisted radical cystectomy aims to reduce postoperative pain and opioid consumption, while facilitating early mobilization and enteral nutrition and minimizing complications. Epidural analgesia is currently recommen...
OBJECTIVES: To analyze the performance of deep learning in isodense/obscure masses in dense breasts. To build and validate a deep learning (DL) model using core radiology principles and analyze its performance in isodense/obscure masses. To show perf...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.