BMC medical informatics and decision making
Feb 3, 2025
INTRODUCTION: Renal transplantation is a critical treatment for end-stage renal disease, but graft failure remains a significant concern. Accurate prediction of graft survival is crucial to identify high-risk patients. This study aimed to develop pro...
BMC medical informatics and decision making
Feb 3, 2025
BACKGROUND: There is no effective way to accurately predict paroxysmal and persistent atrial fibrillation (AF) subtypes unless electrocardiogram (ECG) observation is obtained. We aim to develop a predictive model using a machine learning algorithm fo...
To investigate the feasibility of robot-assisted teleultrasound diagnosis for radioactive patients compared with conventional ultrasound diagnosis. In this prospective study (ChineseClinicalTrials.gov identifier, ChiCTR2200057253), 32 radioactive pat...
Decision-making in chronic diseases guided by clinical decision support systems that use models including multiple variables based on artificial intelligence requires scientific validation in different populations to optimize the use of limited human...
Journal of cancer research and clinical oncology
Feb 3, 2025
OBJECTIVE: The objective of this study is to develop an automated method for segmenting spleen computed tomography (CT) images using a deep learning model. This approach is intended to address the limitations of manual segmentation, which is known to...
People view AI as possessing expertise across various fields, but the perceived quality of AI-generated moral expertise remains uncertain. Recent work suggests that large language models (LLMs) perform well on tasks designed to assess moral alignment...
INTRODUCTION: Oral cancer, especially oral squamous cell carcinoma (OSCC), is a global health challenge due to factors such as late detection and high mortality rates. Early detection is essential through monitoring by healthcare professionals. Cytop...
BACKGROUND AND AIM: Artificial intelligence (AI)-powered chatbots, such as Chat Generative Pretrained Transformer (ChatGPT), have shown promising results in healthcare settings. These tools can help patients obtain real-time responses to queries, ens...
OBJECTIVES: To exploit the capability of super-resolution deep learning reconstruction (SR-DLR) to save radiation exposure from coronary CT angiography (CCTA) and assess its impact on image quality, coronary plaque quantification and characterization...
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