Results 61 to 70 of about 1,097 (213)
Toward Full Interoperability in Materials Science: Integrating Workflows With Knowledge Graphs
The connection of conceptual workflow design, portable execution, and ontology‐based semantics leading to provenance‐rich knowledge graphs are main contributors to interoperability in materials science and a prerequisite to AI‐assisted orchestration and for interoperable Materials Acceleration Platforms.
Jan Janssen +14 more
wiley +1 more source
Background: Health information exchange (HIE) is the electronic exchange of data or information between healthcare institutions, despite the fact that, the format and context of the information may vary.
Raksha Kamath +2 more
doaj +1 more source
A fundamental pre-requisite for the establishment of a scaleable regional health information network (RHIN) is the development of an architectural framework and tools for the integration of specialized autonomous systems and e-health service platforms ...
Manolis Tsiknakis +4 more
doaj +1 more source
Healthcare data warehouse system supporting cross-border interoperability
The free movement of European citizens across member states of the European Union adds an important level of complexity to strategic efforts of health interoperability.
Goce Gavrilov +2 more
doaj +1 more source
Supporting AI Readiness Through Digital Workflows in Materials Science
Digitalization drives innovation in materials science by connecting data silos and turning heterogeneous processes into reusable research pipelines. Across 13 MaterialDigital projects, digital workflows reveal complementary pathways toward AI‐ready materials research, founded on structured data, persistent artifacts, executable orchestration, and ...
Marian Bruns +67 more
wiley +1 more source
Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery
Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang +3 more
wiley +1 more source
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu +3 more
wiley +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Data‐Driven Materials Science for Energy‐Sustainable Applications
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley +1 more source
Importance of achieving semantic interoperability for national health information systems
En el presente artículo se examina de manera general las relaciones entre los dirigentes gubernamentales de las políticas de salud, de los proveedores de cuidado en salud y la adopción de las informaciones de cuidado en salud, así como de las tecnologías
Evelyn Johanna Sophia Hovenga
doaj

