Latest AI and machine learning research in transplantation for healthcare professionals.
BACKGROUND: Vision and vision-language foundation models, a subset of advanced artificial intelligence (AI) frameworks, have shown transformative potential in various medical fields. In ophthalmology, these models, particularly large language models and vision-based models, have demonstrated great potential to improve diagnostic accuracy, enhance treatment planning, and streamline clinical workflo...
INTRODUCTION: Efforts are being made to design a brain-like intelligence due to its robustness, synaptic modification (i.e., learning and memory), analog synaptic multiplication, multi-state storage, ultra-low power consumption, and parallel computation. However, current bioelectronic and biomedical technologies have yet to fully replicate brain-like intelligence. In particular, devices that can e...
PURPOSE: The PET Response Criteria in Solid Tumours (PERCIST) 1.0 provides a standardized framework for evaluating treatment response using [18F]fluor...
This paper investigates the distributed variational generalized Nash equilibrium (vGNE) seeking problem for nonsmooth noncooperative game. Specificall...
OBJECTIVE: To develop and rigorously validate radiomics-based predictive models using postoperative intravoxel incoherent motion diffusion-weighted im...
OBJECTIVES: To present a publicly available deep learning-based torso segmentation model that provides comprehensive voxel-wise coverage, including de...
BACKGROUND: The automated segmentation of maxillary and mandibular bones in cone-beam computed tomography (CBCT) using artificial intelligence (AI) is...
Breast cancer is the most commonly diagnosed cancer among women worldwide, and concerns regarding radiation exposure from mammography screening remain...
Lead (Pb), a heavy metal with extensive industrial applications, poses significant risks to human health and the environment. These detrimental effect...
PURPOSE: The clinical significance of medullary abnormalities in the appendicular skeleton detected by computed tomography (CT) in patients with multi...
For ensuring blood safety, potential blood donors undergo comprehensive eligibility screening, comprising a review of their medical history and a phys...
Early detection and accurate classification of retinal diseases, such as diabetic retinopathy (DR) and age-related macular degeneration (AMD), are ess...
Deep incremental hashing can generate hash codes incrementally for new classes, while keeping the existing ones unchanged. Existing methods typically ...
PURPOSE: Four-dimensional computed tomography (4D CT) imaging is essential for radiation therapy planning in thoracic tumors. However, current protoco...
BACKGROUND: Sepsis in immunosuppressed patients is associated with significantly higher mortality rates, yet predictive models tailored to this high-r...
ETHNOPHARMACOLOGICAL RELEVANCE: Sepsis is a life-threatening condition resulting from an uncontrolled immune response to infection, leading to organ d...
Large language models (LLMs) have been successfully used for data extraction from free-text radiology reports. Most current studies were conducted wit...
PURPOSE: Tebentafusp has emerged as the first systemic therapy to significantly prolong survival in treatment-naïve HLA-A*02:01 + patients with unrese...
BACKGROUND: Ideal tip projection and rotation in rhinoplasty often requires placement of caudal septal extension grafts (CSEGs). Although CSEGs are ub...
Deep learning has the potential to be a powerful tool for automating allele calling in forensic DNA analysis. Studies to date have relied on bespoke m...