Results 191 to 200 of about 874,982 (263)

Learning Crystallographic Disorder: Bridging Prediction and Experiment in Materials Discovery

Advanced Materials, EarlyView.
Machine learning based computational materials discovery workflows have recently proposed thousands of potentially stable crystalline materials. However, the experimental realization of these predictions is often challenging because the models assume perfectly ordered structures.
Konstantin S. Jakob, Aron Walsh, Karsten Reuter, Johannes T. Margraf   +3 more
wiley   +1 more source

Machine learning and nomogram prediction model to explore the relationship between monocyte-to-high-density lipoprotein cholesterol ratio and asthma: results from the NHANES 2001-2018. [PDF]

Eur J Med Res
Zou L, Zhao J, Ruan Y, Wang Y.
europepmc   +1 more source

Stacked ensemble machine learning approach for electroencephalography based major depressive disorder classification using temporal statistics

N. Ahmed, Tejas Kadengodlu Bhat, Omkar S Powar   +2 more
openalex   +1 more source

Review of Multifunctional Neural Probe

Advanced Materials Interfaces, EarlyView.
Modern multifunctional neural probes for brain‐machine interfaces extend beyond basic electrical functions to incorporate chemical and optical modalities. This review explores recent advances in multifunctional probes developed for neural signal acquisition and stimulation, highlighting how these innovations enhance the precision of brain activity ...
Ziqi Jia, Yong Kyu Yoon
wiley   +1 more source

Establishment of a Diabetes-Tailored Data Intelligence Platform Enhances Clinical Care, Enables Risk-Based Monitoring, and Facilitates Population-Health-Based Approaches at a Pediatric Diabetes Network. [PDF]

J Diabetes Sci Technol
Lockee B, Vandervelden CA, Tilden DR, Panfil K, Tallon EM, DeWit E, Noland K, Williams DD, Gill H, Patton SR, Prahalad P, Espinoza J, Waghmode A, Barnes M, Clements MA.   +14 more
europepmc   +1 more source

Lipid discovery enabled by sequence statistics and machine learning

Priya M. Christensen, Jonathan Martin, Aparna Uppuluri, Luke R. Joyce, Yahan Wei, Ziqiang Guan, Faruck Morcos, Kelli L. Palmer   +7 more
openalex   +1 more source

Vertical Nanostructures as Novel Interfaces for Brain Research

Advanced Materials Interfaces, EarlyView.
This review highlights the unique features of vertical nanostructures (nanoneedles, nanostraws, nanopillars, and nanowires) for applications in brain research. Various characteristics of nanostructures, including material selection, fabrication methodology, and geometric designs, are discussed for their specific use in neurite guidance, neuron pinning,
Hao Nguyen Tran, Andrea J. O'Connor, Chennupati Jagadish, Vini Gautam   +3 more
wiley   +1 more source

Estimating the peak age of chess players through statistical and machine learning techniques. [PDF]

Sci Rep
Erilli NA, Dalar AZ.
europepmc   +1 more source

Antimicrobial Multi‐Assay Evaluation of (Al‐Doped ZnO)‐Ag and TiO2‐Ag Nanocoatings: Impact of Direct and Indirect Mechanisms

Advanced Materials Interfaces, EarlyView.
This work explores the antimicrobial action of AZO‐Ag and TiO2‐Ag nanocoatings on plastic, demonstrating good efficacy against highly‐critical antibiotic‐resistant bacteria, yeast, and virus. A multi‐assay approach is here exploited to inspect the contribution of direct and indirect antimicrobial mechanisms, and potential human toxicity is also ...
Damiano Squitieri, Roberta Vitali, Cecilia Bartoleschi, Giulia Lombardini, Margherita Cacaci, Lorenzo Degli Esposti, Camilla Fusacchia, Skerxho Osmani, Luca Gavioli, Francesca Bugli, Daniele Valerini   +10 more
wiley   +1 more source

Machine learning based prediction of low birth weight and its associated risk factors: Insights from the Bangladesh Demographic and Health Survey 2022. [PDF]

PLOS Glob Public Health
Sultana N, Afia Z, Sifat IK, Zoha S, Jisa TA, Kibria MK.   +5 more
europepmc   +1 more source