Latest AI and machine learning research in pain management for healthcare professionals.
Recent multimodal large language models (MLLMs) have made remarkable progress on fine-grained perception tasks under the "Thinking with Images" (TwI) paradigm by iteratively performing various visual tool operations. However, this paradigm relies heavily on frequent external tool calls and repeated image re-encoding, which leads to substantial computational overhead and inference latency. To addre...
Vision language models (VLMs) have made remarkable progress in visual reasoning during the last decade. Most evaluations have used simple scenes (MS-COCO) that do not showcase complex human interactions or behaviors, only a handful of non-curated human descriptions as a benchmark, and have not focused on understanding the model's error types. Here, we introduce the Complex Social Behavior (CSB) da...
BACKGROUND Accurate differential diagnosis of complex neurological disorders remains challenging due to overlapping clinical features and heterogeneou...
The ability to extract and exploit temporal structure across diverse tasks is central to human cognition. Neuroscientists have typically relied on rec...
Objective. To evaluate whether open-weight large language models (LLMs) can accurately extract clinical findings from Finnish-language pediatric recor...
The complementary information between RGB and IR images can significantly enhance object detection performance under extreme conditions. Existing meth...
Enhancing images to make them visually appealing is a persistent challenge in computer vision. Many deep-learning methods train models on paired datas...
Exogenous opioids that activate mu-opioid receptors (MORs) in nociceptive circuits mediate transient pain relief lasting minutes to hours but have mor...
Molecular property prediction often relies on isolated data modalities, where continuous 3D graph neural networks (GNNs) struggle to efficiently captu...
3D Gaussian Splatting provides an explicit representation that jointly models geometry and appearance, serving as a scalable foundation for 3D represe...
Fine-grained image recognition poses a significant challenge due to the substantial expertise and effort required for manual annotation. Vision-langua...
Transformer architectures have shown strong potential in time series forecasting, where multi-head self-attention is widely used to capture temporal d...
Background: Heart failure (HF) and chronic obstructive pulmonary disease (COPD) are among the leading causes of morbidity and mortality globally, with...
Chemotherapy-induced peripheral neuropathy (CIPN) is a common and painful side effect of paclitaxel (PTX) treatment. The most common measures of painf...
Rehabilitation exercises are essential in restoring lost physical functions of patients suffering from various diseases (e.g., Parkinson's, back pain)...
Homography estimation, as one of the fundamental problems in computer vision, remains challenged by scale variation scenarios where image pairs potent...
To address data overload and inefficient shape-level annotation in robotic visual inspection, this paper proposes a hardware-software integrated optoe...
Background Conventional rodent models for the study of corneal pain commonly evoke eye blink reflex using methods that indiscriminately activate polym...
The integration of visual evidence has significantly enhanced the capabilities of large multimodal models. However, this integration predominantly rel...
Can one graph represent every kind of LLM agent's run? A trace records what each step did, never what it relied on, the state it read, and the results...