Results 191 to 200 of about 1,141,752 (328)

Engineered Microfluidic Organoid Systems: New Paradigms for Menopause Mechanism Research and Personalized Medicine

Advanced Materials Technologies, EarlyView.
This review explores the integration of microfluidic technology with organoid systems as an innovative platform for studying menopausea complex multi‐organ condition. By enabling precise simulation of inter‐organ communication and hormone responses, microfluidic organoids offer a physiologically relevant model for investigating menopausal syndrome and ...
Qianyi Zhang, He Huang, Hongliang Dong, Qiang Ma, Hongyan Jin   +4 more
wiley   +1 more source

Feasibility of real-time compression frequency and compression depth assessment in CPR using a "machine-learning" artificial intelligence tool. [PDF]

Resusc Plus
Ecker H, Adams NB, Schmitz M, Wetsch WA.
europepmc   +1 more source

Degradation Mechanisms in PEM Water Electrolysis: Diagnosis and Impact

Advanced Materials Technologies, EarlyView.
This review provides an analysis of degradation mechanisms in proton electrolyte membrane water electrolyzers (PEMWE), focusing on all key components. It discusses diagnostic and measurement techniques for evaluating degradation, less‐studied mechanisms, and an expert survey.
Annik Bernhardt, Katja Lange, Robert Göckeritz, Erik Grunwald, Angelika Hähnel, Alexander Müller, Volker Naumann, Sistan Rasuli, Wolfram Münchgesang, Bruno G. Pollet, Kerstin Witte‐Bodnar, Klemens Ilse   +11 more
wiley   +1 more source

The principle of uncertainty in biology: Will machine learning/artificial intelligence lead to the end of mechanistic studies? [PDF]

PLoS Biol
de Lorenzo V.
europepmc   +1 more source

Hydrogel‐Based Functional Materials: Classifications, Properties, and Applications

Advanced Materials Technologies, EarlyView.
Conductive hydrogels have emerged as promising materials for smart wearable devices due to their outstanding flexibility, multifunctionality, and biocompatibility. This review systematically summarizes recent progress in their design strategies, focusing on monomer systems and conductive components, and highlights key multifunctional properties such as
Zeyu Zhang, Zao Cheng, Patrizio Raffa
wiley   +1 more source

Non-invasive derivation of instantaneous free-wave ratio from invasive coronary angiography using a new deep learning artificial intelligence model and comparison with human operators' performance. [PDF]

Int J Cardiovasc Imaging
Oliveira C, Vilela M, Silva Marques J, Jorge C, Rodrigues T, Francisco AR, Oliveira RM, Silva B, Silva JL, Oliveira AL, Pinto FJ, Nobre Menezes M.   +11 more
europepmc   +1 more source

Deep transfer learning artificial intelligence accurately stages COVID-19 lung disease severity on portable chest radiographs. [PDF]

PLoS One, 2020
Zhu J, Shen B, Abbasi A, Hoshmand-Kochi M, Li H, Duong TQ.   +5 more
europepmc   +1 more source

Artificial Intelligence-Driven Deep Learning for Predicting Copper Adsorption on Zeolite-Silver Nanocomposites in Sustainable Water Treatment

Alvaro de Jesus Ruiz - Baltazar
openalex   +1 more source

Artificial intelligence. Machine learning

Vehicle and Electronics. Innovative Technologies, 2019
openaire   +2 more sources

Cap‐oPMN: Oral Inflammatory Load Quantification Using Capillary Microfluidics and Automated Image Processing

Advanced Materials Technologies, EarlyView.
ABSTRACT Quantifying oral polymorphonuclear neutrophils (oPMNs) is a clinically validated approach for assessing periodontal inflammation. However, current methods, such as manual hemocytometry and flow cytometry, are time‐consuming (>3 h), require invasive sampling, and depend on staining and complex instrumentation, making them unsuitable for point ...
Mohsen Hassani, Azam Zare, Fatemeh Soheili, S. M. Mahdi H. Daneshvar, Mahdi Amrollahi Biouki, Yasaman Tahernezhad, Chunxiang Sun, Michael Glogauer, Ebrahim Ghafar‐Zadeh, Amir Sanati‐Nezhad   +9 more
wiley   +1 more source