Results 191 to 200 of about 2,986,386 (301)

Intelligent Lung Support in the Intensive Care Unit (IntelliLung): study protocol for an international observational, prospective, multicentre study. [PDF]

BMJ Open
Theilen R, Huhle R, Scharffenberg M, Fischer F, Kramer T, Koch T, Ball L, Blanch L, Sarlabous L, Suárez-Sipmann F, Szuldrzynski K, Jankowski M, Kalinka J, Trips E, Djawid B, Tsurkan S, Janev V, Nenadović M, Paunović D, Vahdati S, Castells JM, Kurz A, Hallawa A, Serpa Neto A, Schultz MJ, Gama de Abreu M, Wittenstein J, IntelliLung Consortium.   +27 more
europepmc   +1 more source

Automating Chemical Reasoning in High‐Throughput Phase Identification With a Probabilistic, LLM‐Guided Framework

Advanced Science, EarlyView.
Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi, Lauren N. Walters, Amalie E. Trewartha, Steven B. Torrisi, Amanda Volk, Liam Joyce, Gerbrand Ceder, Anubhav Jain   +7 more
wiley   +1 more source

AI-Enabled Interpretation Guidance for Hemostasis Testing with TEG^® 6s. [PDF]

Diagnostics (Basel)
Hartmann J, Souter D, Dias JD, Sha Q.
europepmc   +1 more source

Herbicide Metabolic Resistance in Poaceae Plants via the GA‐GID1/DELLA‐DOF2‐P450s Module

Advanced Science, EarlyView.
Plant hormone signaling modulates herbicide resistance in Echinochloa crus‐galli. The GA–DELLA–DOF2 cascade directly activates P450 detoxification genes in two Poaceae species, uncovering a core mechanism of metabolic herbicide resistance. ABSTRACT Barnyard grass (Echinochloa crus‐galli) is one of the world's most important weeds, and the evolution of ...
Junzhi Wang, Jiale Qi, Lin Wei, Qin Yu, Zhongyuan Liu, Lianyang Bai, Lang Pan   +6 more
wiley   +1 more source

Artificial Intelligence Reporting Guidelines in Dentomaxillofacial Radiology: Specialty-Oriented Practical Guide. [PDF]

Diagnostics (Basel)
Barioni ED, de Oliveira LAP, Santos MMA, Orhan K, de Castro Lopes SLP, Costa ALF.   +5 more
europepmc   +1 more source

Porous Ultralow‐κ sp2‐Bonded Boron Nitride Thin Films as Copper Diffusion Barriers

Advanced Science, EarlyView.
Porous sp2‐bonded boron nitride (p‐BN) thin films with an ultralow dielectric constant (κ = 1.77) are directly grown on Si substrates via RF magnetron sputtering. The films feature uniform nanopores (1.85 nm), high mechanical stability, hydrophobicity, and excellent Cu diffusion barrier performance even at 3 nm thickness, offering a promising solution ...
Caiyun Liu, Ze Long, Zhongyuan Han, Yingying Guo, Yuning Ding, Tianhao Guo, Yuting Tang, Runzhi An, Haoran Ma, Jishan Liu, Hongwei Liang, Hong Yin   +11 more
wiley   +1 more source

Are artificial intelligence-generated recommendations clinically safe? Evaluation of thromboembolic prophylaxis advice after arthroplasty. [PDF]

Rev Assoc Med Bras (1992)
Polat Ö, Dünki A, Aydin MT, Çamur S.
europepmc   +1 more source

SemanticST: A Scalable Multi‐Contextual Graph Learning Framework for Uncovering Spatial Niches and Robust Multi‐Sample Integration in Spatial Transcriptomics

Advanced Science, EarlyView.
Technical limitations often let dominant signals overshadow rare cell types and fine‐grained heterogeneity in spatial transcriptomics. SemanticST, a graph neural network using multi‐semantic graph fusion and a novel min‐cut loss, recovers these subtle patterns.
Roxana Zahedi, Ahmadreza Argha, Nona Farbehi, Ivan Bakhshayeshi, Thantrira Porntaveetus, Youqiong Ye, Nigel H. Lovell, Hamid Alinejad‐Rokny   +7 more
wiley   +1 more source

Are We Prepared for Agentic Dentistry? Exploring the Impact of Autonomous Artificial Intelligence in Dental Care. [PDF]

Int Dent J
Turky M, Dummer PMH.
europepmc   +1 more source

The State of AI Recommendations in Pets

This study examines whether AI recommendation frequency is related to ecommerce store readiness in the pet category. Using one AI model (GPT-4o-mini), 20 high-intent pet shopping prompts were each run 20 times, producing 4,000 captured recommendations across 405 distinct brands.
openaire   +1 more source