Results 181 to 190 of about 592,656 (330)

Illuminating the Interface of Blocc Chemistry and Data Science: An Introduction to K‑Nearest Neighbor Analysis and K‑Medoids Clustering. [PDF]

J Chem Educ
Green NM, Putnam JLB, Hammond RI, Angello NH, Planey J, Brandt D, Martinez JA, Hummel T, Gunasekera B, Switzky R, Desmond S, Burke MD.   +11 more
europepmc   +1 more source

Robust and efficient single-cell Hi-C clustering with approximate k-nearest neighbor graphs. [PDF]

Bioinformatics, 2021
Wolff J, Backofen R, Grüning B.
europepmc   +1 more source

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

Boosting K-nearest neighbor regression performance for longitudinal data through a novel learning approach. [PDF]

BMC Bioinformatics
Loeloe MS, Tabatabaei SM, Sefidkar R, Mehrparvar AH, Jambarsang S.   +4 more
europepmc   +1 more source

KNNCNV: A K-Nearest Neighbor Based Method for Detection of Copy Number Variations Using NGS Data. [PDF]

Front Cell Dev Biol, 2021
Xie K, Liu K, Alvi HAK, Chen Y, Wang S, Yuan X.   +5 more
europepmc   +1 more source

Golden‐Ratio–Guided Aperiodic Architected Metamaterials with Simultaneously Enhanced Strength and Toughness

Advanced Functional Materials, EarlyView.
Guided by the golden ratio, a class of aperiodic architected metamaterials is introduced to address the intrinsic trade‐off between strength and toughness. By unifying local geometric heterogeneity with global order, the golden‐ratio‐guided aperiodic architecture promotes spatial delocalization of damage tolerence regions, leading to more tortuous ...
Junjie Deng, Xinxin Wang, Ruochao Zhao, Zhendong Li, Kai Liu, Ke Yuan, Jia An, Xinwei Li, Chee Kai Chua, Zhonggang Wang   +9 more
wiley   +1 more source

Machine learning estimating paracetamol solubility in supercritical CO₂ by utilization of K-nearest neighbor regression and metaheuristic algorithms. [PDF]

Sci Rep
Thajudeen KY, Alshehri SA, Rahamathulla M, Ahmed MM.   +3 more
europepmc   +1 more source

Segmentation of Organs and Tumor within Brain Magnetic Resonance Images Using K-Nearest Neighbor Classification. [PDF]

J Med Phys, 2022
Yoganathan SA, Zhang R.
europepmc   +1 more source

Tailoring Microstructure in Copper‐Based Conductive Metal–Organic Frameworks for Enhanced Chemiresistive Sensing and Uptake of Sulfur Dioxide

Advanced Functional Materials, EarlyView.
Precursor‐ and solvent‐mediated synthesis yields four Cu3(HHTP)2 morphologies with distinct physicochemical, sorption, and sensing properties toward SO2. Uptake capacities correlate with BET surface area, while sensing performance scales with particle aspect ratio.
Patrick Damacet, Zhuoran Zhong, Elí Sánchez‐González, Camille L. Slagle, Ilich A. Ibarra, Katherine A. Mirica   +5 more
wiley   +1 more source

Predicting and classifying type 2 diabetes using a transparent ensemble model combining random forest, k-nearest neighbor, and neural networks. [PDF]

Sci Rep
Zaferani N, Afrash MR, Moulaei K.
europepmc   +1 more source