Results 221 to 230 of about 373,459 (274)

Medicines, Diseases, Indications, and Contraindications (MeDIC): a foundational resource to support drug repurposing. [PDF]

Nucleic Acids Res
DeLuca M, Matentzoglu N, Sharp E, Li J, Hempstead C, Lim M, Kaniewski P, Carter EK, Koirala K, Ding E, Vijnck L, Brokmeier P, Toro S, Schaper K, Vergine J, Li O, Oprea TI, Fajgenbaum DC, Bizon C, Haendel M, Tropsha A.   +20 more
europepmc   +1 more source

The Necessity of Dynamic Workflow Managers for Advancing Self‐Driving Labs and Optimizers

Advanced Intelligent Discovery, EarlyView.
We assess the maturity and integration readiness of key methodologies for Materials Acceleration Platforms, highlighting the need for dynamic workflow managers. Demonstrating this, we integrate PerQueue into a color‐mixing robot, showing how flexible orchestration improves coordination and optimization.
Simon K. Steensen, Patrick W. V. Butler, Jesper R. Pedersen, Nis Fisker‐Bødker, Tejs Vegge, Jin Hyun Chang, Ivano E. Castelli   +6 more
wiley   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source

Comment on "Periodontitis and Oral Cancer" by Xia and Song. [PDF]

Int Dent J
Somay E, Bascil S.
europepmc   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

Research on the construction and application of retrieval enhanced generation (RAG) model based on knowledge graph. [PDF]

Sci Rep
Wang S, Yang H, Liu W.
europepmc   +1 more source

Evolution of Physical Intelligence Across Scales

Advanced Intelligent Discovery, EarlyView.
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu, Tianyun Huang, Aming Li, Pengyu Lv, Tingting Qin, Wenhui Chen, Hui Wei, Huiling Duan   +7 more
wiley   +1 more source

Grammar error diagnosis using graph convolutional networks with knowledge graph integration. [PDF]

Sci Rep
Zhang J, Ma Y.
europepmc   +1 more source

Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents

Advanced Intelligent Discovery, EarlyView.
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer, Muhammad Nabeel Asim, Shan Munir, Andreas Dengel   +3 more
wiley   +1 more source

Transformer-based relation extraction and concept normalization using an annotated clinical trials corpus. [PDF]

Sci Data
Campillos-Llanos L, Valverde-Mateos A, Capllonch-Carrión A, González-Quevedo D, López-Urbán MR, Hernando-Tundidor MS, Zakhir-Puig S, Heras J.   +7 more
europepmc   +1 more source