Latest AI and machine learning research in prescriptions for healthcare professionals.
Medication product names in Swiss electronic health records are heterogeneous and often encode multiple attributes (e.g., ingredient, strength, dose form, packaging) in German free text. This limits interoperability and reduces the utility of ATC codes, which do not uniquely identify products. We compared two workflows for mapping Swiss medication products to RxNorm and RxNorm Extension: (i) an Ob...
Background/ObjectivesHead and neck cancer (HNC) represents the seventh most common cancer diagnosis globally, yet current treatments, including surgery, radiation, and immunotherapy, have shown limited improvement in outcomes. Drug repurposing offers a cost-effective strategy to identify new therapeutic options by leveraging existing medications with known safety profiles. Within this study we dev...
Inverse design tools such as Topology Optimization (TO) can achieve new levels of improvement for high-performance engineered structures. However, wid...
BackgroundThe accuracy and safety of generating medication orders by large language models (LLMs) must be demonstrated. Without standardization, perfo...
Egocentric Human-Object Interaction (EHOI) analysis is crucial for industrial safety, yet the development of robust models is hindered by the scarcity...
Recent progress in medical vision-language models (VLMs) has achieved strong performance on image-level text-centric tasks such as report generation a...
Osteosarcoma (OS) is an aggressive bone cancer that mainly occurs in children and adolescents. OS patients are mainly treated with neoadjuvant chemoth...
The binding of zinc ions to proteins plays a crucial role in normal physiological functions and life activities of organisms. To enhance the predictio...
TAK1, a multifunctional kinase, possesses intramolecular interactions that are capacitated to recognize and process diverse forms of chemical and mech...
This study investigates the potential of a multimodal large language model (LLM), specifically ChatGPT-4o, to perform human-like interpretations of ...
Large language model (LLM) chatbots show increasing promise in persuasive communication. Yet their real-world utility remains uncertain, particularl...
Drug Mechanism of Action (MoA) mainly investigates how drug molecules interact with cells, which is crucial for drug discovery and clinical applicat...
Recent investigations on the effectiveness of Graph Neural Network (GNN)-based models for link prediction in Knowledge Graphs (KGs) show that vanill...
In recent years, large-scale pre-trained multimodal models (LMMs) generally emerge to integrate the vision and language modalities, achieving consid...
Recent advances in image generation models (IGMs), particularly diffusion-based architectures such as Stable Diffusion (SD), have markedly enhanced ...
Learning cross-modal correspondences is essential for image-to-point cloud (I2P) registration. Existing methods achieve this mostly by utilizing met...
We introduce MOST, a novel motion diffusion model via temporal clip Banzhaf interaction, aimed at addressing the persistent challenge of generating ...
Open vocabulary Human-Object Interaction (HOI) detection is a challenging
task that detects all
We proposed presenting a novel integrated platform, ExposomeX, that was created to expedite discovery of the "exposure-biology-disease" nexus. This pl...
Hallucinations in large vision-language models (LVLMs) pose significant challenges for real-world applications, as LVLMs may generate responses that...