Latest AI and machine learning research in identifying and reporting dependent adult abuse for healthcare professionals.
In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(...
Political bias is an inescapable characteristic in news and media reporting, and understanding what political biases people are exposed to when interacting with online news is of crucial import. However, quantifying political bias is problematic. To systematically study the political biases of online news, much of previous research has used human-labelled databases. Yet, these databases tend to be...
The primary challenge of cross-domain few-shot segmentation (CD-FSS) is the domain disparity between the training and inference phases, which can ex...
MOTIVATION: T-cell receptors (TCRs) elicit and mediate the adaptive immune response by recognizing antigenic peptides, a process pivotal for cancer im...
The in-image machine translation task involves translating text embedded within images, with the translated results presented in image format. While...
Few-shot anomaly detection (FSAD) aims to detect unseen anomaly regions with the guidance of very few normal support images from the same class. Exi...
When given two similar images, humans identify their differences by comparing the appearance ({\it e.g., color, texture}) with the help of semantics...
Direct Preference Optimization (DPO) has been demonstrated to be highly effective in mitigating hallucinations in Large Vision Language Models (LVLM...
Human trafficking (HT) remains a critical issue, with traffickers increasingly leveraging online escort advertisements (ads) to advertise victims an...
Images captured in severe low-light circumstances often suffer from significant information absence. Existing singular modality image enhancement me...
Recent medical vision-language models (VLMs) have shown promise in 2D medical image interpretation. However extending them to 3D medical imaging has...
Medical image segmentation is crucial in modern medical image analysis, which can aid into diagnosis of various disease conditions. Recently, langua...
Infrared-visible object detection (IVOD) seeks to harness the complementary information in infrared and visible images, thereby enhancing the perfor...
The reproducibility of computational pipelines is an expectation in biomedical science, particularly in critical domains like human health. In this ...
The subtlety of emotional expressions makes implicit emotion analysis (IEA) particularly sensitive to user-specific characteristics. Current studies...
Single image super-resolution (SR) has long posed a challenge in the field of computer vision. While the advent of deep learning has led to the emer...
Recent research on real-time object detectors (e.g., YOLO series) has demonstrated the effectiveness of attention mechanisms for elevating model per...
We propose a pipeline for gaining insights into complex diseases by training LLMs on challenging social media text data classification tasks, obtain...
The advancement of Large Vision-Language Models (LVLMs) has propelled their application in the medical field. However, Medical LVLMs (Med-LVLMs) enc...
In medical reporting, the accuracy of radiological reports, whether generated by humans or machine learning algorithms, is critical. We tackle a new...