Latest AI and machine learning research in heart transplantation for healthcare professionals.
Kidney transplant recipients experience a higher burden of several malignancies, yet the factors associated with prostate cancer presentation after transplantation remain poorly understood. Unlike malignancies strongly associated with impaired immune surveillance, prostate cancer has not consistently demonstrated an increased incidence after transplantation, suggesting that different mechanisms ma...
We propose RefineSVG, a single-step closed-loop visual feedback framework that enables multimodal large language models (MLLMs) to perform high-fidelity image-to-SVG generation through self-correction. Existing MLLM-based approaches rely on single-pass open-loop inference, where the model receives visual input only once and must generate thousands of SVG code tokens without intermediate verificati...
Existing video captioning models generate natural descriptions of video content but cannot explicitly ground local visual elements to multiple referen...
The introduction of LAFOV PET scanners brings significant sensitivity gains but also a substantial increase in the background rate from accidental coi...
Standard uncertainty-informed rejection can unexpectedly trigger severe performance collapse, exposing localized vulnerabilities that common machine l...
Preformed and de novo antibodies against donor human leukocyte antigen (HLA) antigens remain a major cause of antibody-mediated rejection and graft lo...
A surveillance camera is an image sensor whose silent physical degradation invalidates every downstream consumer of its data. In-situ integrity alarms...
Knowledge-based Visual Question Answering (KB-VQA) requires models to retrieve visual entities matching the query image from large-scale encyclopedic ...
Recent advances in generative Artificial Intelligence have made synthetic face images increasingly realistic, creating new challenges for multimedia f...
Unplanned readmissions after liver transplantation occur in over 30% of recipients, yet no validated prediction models exist, and prior observational ...
Intelligent industrial maintenance critically relies on reliable fault diagnosis of rotating machinery. However, it faces formidable challenges from u...
Text-rich image generation is one of the most challenging settings in image generation, since models must simultaneously produce visually realistic im...
Unified visual anomaly detection seeks to train a single detector that can be deployed across categories, domains, and application scenarios. In the f...
Knowledge-based Visual Question Answering (KB-VQA) requires models to combine image understanding with external knowledge. Most prior methods use a fi...
Facial expression recognition (FER) is inherently ambiguous: human annotators frequently disagree, and models deployed in real environments face distr...
The identification of small molecule modulators of immune checkpoint proteins remains a significant challenge in drug discovery due to the flat, featu...
Style-content dual-reference generation aims to synthesize an image that preserves the structure and semantics of a content reference while adopting t...
Reject inference methods are widely used to mitigate survival bias in credit scoring, yet their effectiveness remains poorly understood. We systematic...
Translating high-dimensional, spatially resolved molecular datasets into testable biological findings remains a major research bottleneck. Here, we pr...
AI is increasingly used to support scientific peer review, from manuscript screening, reviewer assistance to editorial triage. Although such systems p...