Results 141 to 150 of about 430,392 (288)

Miliary tuberculosis with bilateral adrenal involvementand adrenal insufficiency. [PDF]

Rev Soc Bras Med Trop
Yeşilyurt M, Karaman A.
europepmc   +1 more source

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

Arthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +1 more source

EEG for bedside monitoring: the intensivist's point of view. [PDF]

Crit Care
Taccone FS, Ozkaya T, Baggiani M, Rasulo FA.   +3 more
europepmc   +1 more source

Harnessing Fungal Biowelding for Constructing Mycelium‐Engineered Materials

Advanced Engineering Materials, EarlyView.
Mycelium‐bound composites (MBCs) offer low‐carbon alternatives for construction, yet interfacial bonding remains a critical challenge. This review examines fungal biowelding as a biocompatible adhesive, elucidating mycelium‐mediated interfacial mechanisms and their role in material assembly. Strategies to optimize biowelding are discussed, highlighting
Xue Brenda Bai, Xinrui Sarah Niu, Zhao Qin   +2 more
wiley   +1 more source

AI-Enhanced POCUS in Emergency Care. [PDF]

Diagnostics (Basel)
Puticiu M, Cimpoesu D, Pop F, Ciumanghel I, Rotaru LT, Oprita B, Butoi MA, Belghiru VI, Tat RM, Golea A.   +9 more
europepmc   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Rethinking pattern hair loss classification in the era of trichoscopy and artificial intelligence. [PDF]

Front Med (Lausanne)
Sánchez-Dueñas LE, León Quintero-Loreto M, Moreno-Alanis JA, Quiñones-Hernández DG, Larios-Cárdenas M.   +4 more
europepmc   +1 more source

On the Lightweight Potential of Laser Additive Manufactured NiTi Triply Periodic Minimal Sheet Lattices

Advanced Engineering Materials, EarlyView.
This study explores the lightweight potential of laser additive‐manufactured NiTi triply periodic minimal surface sheet lattices. It systematically investigates the effects of relative density and unit cell size on surface quality, deformation recovery, compression behavior, and energy absorption.
Haoming Mo, Shuo Qu, Shiming Gao, Xu Song   +3 more
wiley   +1 more source

Services for Connected, Cooperated, and Automated Mobility based on Big Data and Artificial Intelligence: The SHOW project paradigm. [PDF]

Open Res Eur
Spanos G, Siomos A, Schmidt C, Tygesen M, Salanova JM, Rodrigues F, Papadopoulos A, Antypas E, Sersemis A, Gkemou M, Lalas A, Votis K, Ayfantopoulou G, Bekiaris E, Tzovaras D.   +14 more
europepmc   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source