Latest AI and machine learning research in prescriptions for healthcare professionals.
Accurately predicting drug-drug interactions (DDIs) is crucial for pharmaceutical research and clinical safety. Recent deep learning models often suffer from high computational costs and limited generalization across datasets. In this study, we investigate a simpler yet effective approach using molecular representations such as Morgan fingerprints (MFPS), graph-based embeddings from graph convol...
In the pursuit of deeper immersion in human-machine interaction, achieving higher-dimensional tactile input and output on a single interface has become a key research focus. This study introduces the Visual-Electronic Tactile (VET) System, which builds upon vision-based tactile sensors (VBTS) and integrates electrical stimulation feedback to enable bidirectional tactile communication. We propose...
Product recalls provide valuable insights into potential risks and hazards within the engineering design process, yet their full potential remains u...
Large language models (LLMs) have shown remarkable capabilities in solving complex tasks. Recent work has explored decomposing such tasks into subta...
Knowledge graphs and large language models (LLMs) are key tools for biomedical knowledge integration and reasoning, facilitating structured organiza...
MOTIVATION: Identifying drug-target interactions (DTIs) is a crucial step in drug repurposing and drug discovery. The significant increase in demand a...
SUMMARY: The lit-OTAR framework, developed through a collaboration between Europe PMC and Open Targets, leverages deep learning to revolutionize drug ...
Study Design: The study outlines the development of an autonomous AI system for chest X-ray (CXR) interpretation, trained on a vast dataset of over ...
Human interactions in everyday life are inherently social, involving engagements with diverse individuals across various contexts. Modeling these so...
We introduce a novel task of generating realistic and diverse 3D hand trajectories given a single image of an object, which could be involved in a h...
Free tensors are tensors which, after a change of bases, have free support: any two distinct elements of its support differ in at least two coordina...
Pre-trained conditional diffusion models have demonstrated remarkable potential in image editing. However, they often face challenges with temporal ...
When faced with complex and uncertain medical conditions (e.g., cancer, mental health conditions, recovery from substance dependency), millions of p...
Pavement distress, such as cracks and potholes, is a significant issue affecting road safety and maintenance. In this study, we present the implemen...
In a context of constant increase in competition and heightened regulatory pressure, accuracy, actuarial precision, as well as transparency and unde...
Background Telemedicine has the potential to provide secure and cost-effective healthcare at the touch of a button. Nephrotic syndrome is a chronic ...
Semantic similarity measures (SSMs) are widely used in biomedical research but remain underutilized in pharmacovigilance. This study evaluates six o...
Reliable drug safety reference databases are essential for pharmacovigilance, yet existing resources like SIDER are outdated and static. We introduc...
Human-object interaction (HOI) synthesis is important for various applications, ranging from virtual reality to robotics. However, acquiring 3D HOI ...
Multimodal social interaction understanding (MMSI) is critical in human-robot interaction systems. In real-world scenarios, AI agents are required t...