Results 191 to 200 of about 6,391,262 (321)
A multi‐fidelity framework integrates sparse direct and abundant indirect electrocaloric measurements. Multi‐objective active learning accelerates BaTiO3‐based electrocaloric materials discovery at –70∘C$^{\circ }{\rm C}$. A diffuse transition enables an electrocaloric strength of 0.06×$\times$10−6 Km/V at –70℃ with an operational temperature span of ...
Bo Wang +8 more
wiley +1 more source
A flexible symbolic regression method for constructing interpretable clinical prediction models. [PDF]
La Cava WG +7 more
europepmc +1 more source
A biomimetic doppelgänger nanosystem neutralizes extracellular inflammatory cytokines and silences intracellular pyroptosis, reprogramming pathogenic macrophages to attenuate both joint and spine degeneration. ABSTRACT Osteoarthritis (OA) and intervertebral disc degeneration (IVDD) are debilitating musculoskeletal disorders driven by shared ...
Fudong Li +9 more
wiley +1 more source
Unsupervised Hierarchical Symbolic Regression for Interpretable Property Modeling in Complex Multi-Variable Systems. [PDF]
Lou S, Liu C, Zhang D, Chen Y, Mo F.
europepmc +1 more source
A computational framework for physics-informed symbolic regression with straightforward integration of domain knowledge. [PDF]
Keren LS, Liberzon A, Lazebnik T.
europepmc +1 more source
A schematic illustrating the fabrication process and ferroptosis‐mediated therapeutic mechanism of carrier‐free self‐assembled BBR/NC‐SAPs for overcoming bortezomib resistance in multiple myeloma. ABSTRACT Therapeutic relapse driven by bortezomib resistance represents a formidable clinical barrier in the management of multiple myeloma (MM).
Yiwen Lv +16 more
wiley +1 more source
Hybrid PSO-SVM and symbolic regression model for agricultural water demand prediction. [PDF]
Lv H, Zhao Y, Wang W, Hou K, Zheng X.
europepmc +1 more source
Contemporary Symbolic Regression Methods and their Relative Performance. [PDF]
La Cava W +7 more
europepmc +1 more source
Temporal Feature Selection with Symbolic Regression
Building and discovering useful features when constructing machine learning models is the central task for the machine learning practitioner. Good features are useful not only in increasing the predictive power of a model but also in illuminating the ...
Fusting, Christopher Winter
core
In microglia, STAT3 upregulates TAB2, which promotes NF‐κB activation through its NZF domain‐mediated recognition of K63‐linked ubiquitin chains, leading to inflammatory cytokine release and subsequent neuronal injury. Lumacaftor suppresses TAB2 expression and directly binds the TAB2‐NZF domain to interrupt K63 ubiquitin recognition, thereby blocking ...
Yanhao Zhao +12 more
wiley +1 more source

