Results 231 to 240 of about 3,398,718 (314)
Predictive factors of Black American emerging adults' psychological flourishing: a random forest analysis. [PDF]
Kebbeh N, Jelsma E.
europepmc +1 more source
ProMetNet introduces a biologically constrained deep learning framework for proteo‐metabolomic integration by embedding Reactome‐derived pathway topology into neural networks. It captures non‐linear molecular dependencies and pathway‐level metabolic reorganization, enabling interpretable discrimination.
Minghui Zhao +6 more
wiley +1 more source
Fetal Acidemia Prediction Using a Random Forest Model With Cumulative Fetal Stress Assessment During Labor. [PDF]
Ito A +5 more
europepmc +1 more source
Vision begins not with images but with change: the retina fires only when something moves, handing the brain a stream of spikes. A neuromorphic imaging system adopts the same strategy—an event sensor that sees like the retina, a spiking network that thinks like the brain—to track and reconstruct fully randomly moving targets through tissue (phantom ...
Ning Zhang, Arto Nurmikko
wiley +1 more source
Analysis of Key Driving Factors for Inpatient Service Experience in Obstetrics and Gynecology Specialized Hospitals Based on Random Forest Algorithm. [PDF]
Binxia L, Lina Y, Xingxing L, Yufan Y.
europepmc +1 more source
Schematic illustration of development of experimental datasets and algorithm models, screening and preparation of the scaffolds and their applications in vivo. ABSTRACT Bone defects require materials with osteogenic, neurogenic, and angiogenic activity, yet designing such materials within high‐dimensional compositional spaces remains challenging. Here,
Kunlu Lin +9 more
wiley +1 more source
Optimising Irish Fen Habitat Mapping: An Evaluation of Temporal Windowing and Spectral Features Using Google Earth Engine and Random Forest. [PDF]
Farrell C +4 more
europepmc +1 more source
Computationally Evidence‐Grounded Sequence‐First Design of Peptide Binders
BOND‐PEP enables controllable, sequence‐first peptide binder design by grounding generation in binding evidence retrieved for each target. It uses topology‐conditioned message passing to integrate relevant peptide examples with the target protein sequence, forming a residue‐level representation that guides the generation of diverse, target‐specific ...
Wenze Ding
wiley +1 more source

