Results 131 to 140 of about 303,332 (290)
Evaluating Casama: Contextualized semantic maps for summarization of lung cancer studies. [PDF]
Garcia-Gathright JI +11 more
europepmc +1 more source
Abstract World markets for quality differentiated agri‐food products are highly competitive, presenting significant challenges for firms aiming to compete effectively. Government agencies and business organizations often implement various export promotion policies to address these challenges.
Nicolás Depetris‐Chauvin +1 more
wiley +1 more source
Creation of Individual Scientific Concept-Centered Semantic Maps Based on Automated Text-Mining Analysis of PubMed. [PDF]
Ilgisonis E +3 more
europepmc +1 more source
Evaluating The Semantic Mapping
Along the increasing of the importance of links in the network of data, they should be considered more in the mapping relational to graph model. Semantic abstraction gaps often occur during the mapping process where the link in the real world is mapped as a node in a graph model.
openaire +2 more sources
Natural speech reveals the semantic maps that tile human cerebral cortex. [PDF]
Huth AG +4 more
europepmc +1 more source
We systematically reviewed conversion therapy for esophageal squamous cell carcinoma and propose a response‐based treatment strategy for cT4b and M1 disease. For cT4b, we emphasize definitive chemoradiotherapy with timed re‐evaluation and selective salvage or chemoselection to surgery; for M1, conversion is reserved for limited‐burden responders with ...
Eisuke Booka, Hiroya Takeuchi
wiley +1 more source
Semantic Mapping in Video Retrieval [PDF]
In the modern world, networked sensor technology makes it possible to capture the world around us in real-time. In the security domain cameras are an important source of information. Cameras in public places, bodycams, drones and recordings with smart phones are used for real time monitoring of the environment to prevent crime (monitoring case); and/or
openaire +1 more source
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing +4 more
wiley +1 more source
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian +12 more
wiley +1 more source

