Results 101 to 110 of about 2,621 (151)

Automated B‐cell and plasma cell identification using unsupervised clustering by FlowSOM and an excel‐based classification model

Cytometry Part B: Clinical Cytometry, EarlyView.
Abstract Manual gating for plasma cell (PC) identification in multiparametric flow cytometry (MFC) is time‐consuming and operator‐dependent, especially when PCs are scarce. Artificial intelligence approaches such as unsupervised clustering (e.g., FlowSOM) map high‐dimensional data that still require expert interpretation.
Ethan James Gantana, Ernest Musekwa, Erica‐Mari Nell, Zivanai Cuthbert Chapanduka   +3 more
wiley   +1 more source

Mode and Ridge Estimation in Euclidean and Directional Product Spaces: A Mean Shift Approach. [PDF]

J Comput Graph Stat
Zhang Y, Chen YC.
europepmc   +1 more source

Beyond BMI: Unsupervised Machine Learning Clustering of Bioelectrical Impedance Phenotypes Is Associated With Weight‐Recovery Trajectories in Anorexia Nervosa

International Journal of Eating Disorders, EarlyView.
ABSTRACT Objective To identify data‐driven body composition phenotypes in patients with moderate‐to‐extreme anorexia nervosa (AN) using machine learning (ML) clustering of bioelectrical impedance analysis (BIA) parameters, and to test whether these phenotypes have specific psychopathological and childhood trauma profiles while correlating with early ...
Emanuele Cassioli, Gaia Maiolini, Eleonora D'Areglia, Livio Tarchi, Eleonora Rossi, Veronica Ceccarelli, Cristiano Dani, Luca Zompa, Chiara Ranieri, Enrico Lodovici, Anita Nannoni, Valdo Ricca, Giovanni Castellini   +12 more
wiley   +1 more source

Chemical space visualization at scale: a survey of end-to-end pipelines and dataset-size archetypes. [PDF]

J Cheminform
AlShammari MM, Alnammi M, Ahmed M.
europepmc   +1 more source

Assessing the accuracy and stability of variable importance in species distribution modelling algorithms through sample perturbations

Ecography, EarlyView.
Variable importance derived from species distribution modelling (SDM) is widely used to identify key environmental drivers of species distributions. However, the reliability of these inferences has rarely been systematically evaluated, particularly with respect to their sensitivity to individual occurrences.
He Wu, Zhaoning Wu, Yunzhi Liu, Wenfang Zhang, Jiechen Wang   +4 more
wiley   +1 more source

Twist Fields in Many-Body Physics. [PDF]

Entropy (Basel)
Doyon B.
europepmc   +1 more source

Scale‐dependent assembly shapes taxon‐dependent responses of soil microbes to island isolation and area

Ecography, EarlyView.
The theory of island biogeography (TIB) remains contentious for microbes, as their immense dispersal potential and microscopic size may decouple diversity from classic isolation/area effects. We explicitly tested TIB scaling rules for soil bacteria and fungi across 20 oceanic islands using a rigorous multi‐scale framework that integrated high ...
Lan Liu, Zuzana Münzbergová, Lele Jiang, Long Chen, Shurong Zhou   +4 more
wiley   +1 more source

Anthropic Activity Markers 2.0: A Shift Towards Compositional Data Analysis. [PDF]

J Archaeol Method Theory
Ruiz-Giralt A, Biagetti S, Lancelotti C, Parque Ó, Koutroumpas A, Rix KS, Ibáñez-Insa J, Madella M.   +7 more
europepmc   +1 more source

Discharge‐Driven Turbo Formation Stabilizes Cathode–Electrolyte Interfaces in Sulfide All‐Solid‐State Batteries

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
This work examines formation protocols for stabilizing the cathode–electrolyte interphase (CEI) in sulfide all‐solid‐state batteries, highlighting a special turbo discharging protocol discovery. The methodologies presented here show strong potential for integration into emerging artificial intelligence–driven frameworks. Formation protocols dictate the
Yuanshun Li, Chanho Kim, Justin G. Connell, Jianlin Li, Wenda Wu, Harry M. Meyer III, Inyoung Jang, Thomas A. Zawodzinski, Guang Yang   +8 more
wiley   +1 more source

Ultrasound-guided closed-loop control of magnetic hydrogel microrobots with adaptive gait switching. [PDF]

Microsyst Nanoeng
Lang X, Chu L, Chi L, Qi C, Kong T, Liu Z.   +5 more
europepmc   +1 more source