Results 161 to 170 of about 130,387 (281)
INB3P is a multimodal framework for blood–brain barrier‐penetrating peptide prediction under extreme data scarcity and class imbalance. By combining physicochemical‐guided augmentation, sequence–structure co‐attention, and imbalance‐aware optimization, it improves predictive performance and interpretability.
Jingwei Lv +11 more
wiley +1 more source
This work establishes a pipeline that transforms fragmented literature into a structured database for graphitic carbon nitride photocatalyst discovery. A prompt‐engineered, cross‐model large language model ensemble automates high‐fidelity extraction, enabling interpretable machine learning to identify dominant performance descriptors. These data‐driven
Dianyuan Li +7 more
wiley +1 more source
Discovering Interpretable Semantics from Radio Signals for Contactless Cardiac Monitoring
This study presents a semantic representation framework for clinically interpretable cardiac monitoring from contactless radio signals. It formulates radio semantic learning as an information‐bottleneck problem and approximates the objective via intra‐modal compression and cross‐modal alignment, structuring radio measurements into meaningful semantic ...
Jinbo Chen +10 more
wiley +1 more source
Biomass‐ and solid waste‐derived sustainable single‐atom catalysts (Sus‐SACs) provide a cost‐effective and renewable approach to catalyst design. This review summarizes precursor selection, including AI‐assisted screening, synthesis strategies with emphasis on ultrafast methods, and advanced characterization techniques.
Hongzhe He +8 more
wiley +1 more source
Retraction notice to "Enhancing lung cancer detection through hybrid features and machine learning hyperparameters optimization techniques" [Heliyon 10 (2024) e26192]. [PDF]
Li L +10 more
europepmc +1 more source
PAIR: Reconstructing Single‐Cell Open‐Chromatin Landscapes for Transcription Factor Regulome Mapping
scATAC‐seq analysis is often constrained by limited sequencing depth, extreme sparsity, and pervasive technical missingness. PAIR is a probabilistic framework that restores scATAC‐seq accessibility profiles by directly modeling the native cell–peak bipartite structure of chromatin accessibility.
Yanchi Su +7 more
wiley +1 more source
Improving air quality prediction using hybrid BPSO with BWAO for feature selection and hyperparameters optimization. [PDF]
Sawah MS +4 more
europepmc +1 more source
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan +8 more
wiley +1 more source
A CNN Hyperparameters Optimization Based on Particle Swarm Optimization for Mammography Breast Cancer Classification. [PDF]
Aguerchi K +3 more
europepmc +1 more source
A smart headband for multimodal physiological monitoring in human exercises
A novel smart headband incorporating a thermal‐sensation‐based electronic skin is presented for continuous and accurate multimodal physiological monitoring, including pulse waveforms, total metabolic energy expenditure, heart rate, and forehead temperature, across both static and dynamic daily activities.
Shiqiang Liu +7 more
wiley +1 more source

