Latest AI and machine learning research in kidney transplantation for healthcare professionals.
The increasing use of tumor sequencing has intensified the need for fast, traceable interpretation of genomic variants. General-purpose large language models can produce fluent answers, but unsupported statements, weak provenance, and stale knowledge limit their suitability for clinical genomics. We developed OncoGenRAG, a research framework that combines a parameter-efficiently fine-tuned BioBERT...
Computer-aided detection (CADe) systems for colonoscopy promise to reduce clinical miss rates, yet reliable real-world deployment remains elusive. This translational gap stems in part from a structural flaw in model development: the reliance on curated datasets that under-represent the long negative stretches and procedure-related artifacts characteristic of routine examinations. Training and eval...
Camouflaged object detection (COD) aims to segment objects that are visually concealed in their surroundings and has attracted increasing attention in...
Kidney transplant recipients experience a higher burden of several malignancies, yet the factors associated with prostate cancer presentation after tr...
We propose RefineSVG, a single-step closed-loop visual feedback framework that enables multimodal large language models (MLLMs) to perform high-fideli...
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...
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...
BackgroundInitiation of emergency dialysis, often requiring temporary catheter owing to unprepared definitive vascular access, is associated with infe...
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...