Results 161 to 170 of about 312,403 (279)

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Colorectal cancer prognosis based on dietary pattern using synthetic minority oversampling technique with K-nearest neighbors approach. [PDF]

Sci Rep
Prasath ST, Navaneethan C.
europepmc   +1 more source

A Novel Hybrid Model for Predicting Blast-Induced Ground Vibration Based on k-Nearest Neighbors and Particle Swarm Optimization. [PDF]

Sci Rep, 2019
Bui XN, Jaroonpattanapong P, Nguyen H, Tran QH, Long NQ.   +4 more
europepmc   +1 more source

Emergent Spin‐Glass Behavior in an Iron(II)‐Based Metal–Organic Framework Glass

Advanced Functional Materials, EarlyView.
A one‐pot, solvent‐free synthesis yields an Fe2+‐based metal‐organic framework (MOF) glass featuring a continuous random network structure. The material exhibits spin‐glass freezing at 14 K, driven by topological‐disorder and short‐range magnetic frustration, showcasing the potential of MOF glasses as a plattform for cooperative magnetic phenomena in ...
Chinmoy Das, Soma Salamon, Joachim Landers, Jan‐Benedikt Weiß, Wen‐Long Xue, Pascal Kolodzeiski, Roman Pallach, Heiko Wende, Sebastian Henke   +8 more
wiley   +1 more source

A novel ranked <i>k</i>-nearest neighbors algorithm for missing data imputation. [PDF]

J Appl Stat
Khan Y, Shah SF, Asim SM.
europepmc   +1 more source

Introduction to machine learning: k-nearest neighbors. [PDF]

Ann Transl Med, 2016
Zhang Z.
europepmc   +1 more source

Auto‐Generated Valence States in Electrocatalysts for Boosting Oxygen and Hydrogen Evolution Kinetics in Alkaline Water/Alkaline Seawater/Simulated Seawater/Natural Seawater

Advanced Functional Materials, EarlyView.
This review systematically highlights the latest achievements in mixed‐valence states relevant to hydrogen and oxygen evolution reactions, providing essential insights into future directions and methods for large‐scale practical implementation. This critical review is expected to provide an overview of recent advancements in diverse valence‐state metal
Jitendra N. Tiwari, Gokul Bhaskaran, Krishan Kumar, Yun Suk Huh, Young‐Kyu Han   +4 more
wiley   +1 more source

Predicting subcellular localization of multisite proteins using differently weighted multi-label k-nearest neighbors sets. [PDF]

Technol Health Care, 2019
Jiang Z, Wang D, Wu P, Chen Y, Shang H, Wang L, Xie H.   +6 more
europepmc   +1 more source

Understanding and Tuning Mobile Interfaces in Ferroelectric Hf0.5Zr0.5O2 Thin Films in Relation to Microstructure

Advanced Functional Materials, EarlyView.
Ferroelectricity in thin HfO2‐based films offers great possibilities for next‐generation neuromorphic memory devices. There, the response to subcoercive voltage signals is driven by the movement of mobile interfaces and their interaction with crystal defects – a yet rather unexplored aspect, which we shed light on and gain new insights into the complex
Maximilian T. Becker, Yoonsang Park, Kihong Kim, Ji Soo Kim, Nives Strkalj, Atif Jan, Giuliana Di Martino, Benson K. Tsai, Haiyan Wang, Ping Lu, Duk‐Hyun Choe, Judith L. MacManus‐Driscoll   +11 more
wiley   +1 more source

Accelerating the K-Nearest Neighbors Filtering Algorithm to Optimize the Real-Time Classification of Human Brain Tumor in Hyperspectral Images. [PDF]

Sensors (Basel), 2018
Florimbi G, Fabelo H, Torti E, Lazcano R, Madroñal D, Ortega S, Salvador R, Leporati F, Danese G, Báez-Quevedo A, Callicó GM, Juárez E, Sanz C, Sarmiento R.   +13 more
europepmc   +1 more source