Results 221 to 230 of about 2,359,523 (296)
FTGRN introduces an LLM‐enhanced framework for gene regulatory network inference through a two‐stage workflow. It combines a Transformer‐based model, pretrained on GPT‐4 derived gene embeddings and regulatory knowledge, with a fine‐tuning stage utilizing single‐cell RNA‐seq data.
Guangzheng Weng +7 more
wiley +1 more source
A novel autonomous robotic colonoscopy is introduced through supervised learning approaches. The proposed system consists of 3 degrees of freedom motorized colonoscope with an integrated navigation module that can infer a target steering point and collision probability.
Bohyun Hwang +3 more
wiley +1 more source
<i>HV&I</i> Reviewer Highlight. [PDF]
Ellis R, Weiss A.
europepmc +1 more source
A data‐efficient artificial intelligence‐assisted framework, which integrates experimental data with machine learning, is developed for the design of bimodal networked dielectric elastomers (DEs) as advanced artificial muscles. It adopts neural networks to predict DEs’ mechanical properties and support vector machines to classify electromechanical ...
Ofoq Normahmedov +8 more
wiley +1 more source
Correction: Overcoming barriers to NHS adoption of innovative IPC products: A qualitative study of SMEs in the Liverpool city region. [PDF]
Linaza RV +12 more
europepmc +1 more source
A Fully Soft Sensing Suit With Optimal Sensor Placement for Real‐Time Motion Tracking
A fully soft, skin‐conformable sensing suit integrating stretchable sensors, liquid metal wiring, and soft electrodes was developed using direct ink writing, with sensor placement optimized through an automated algorithmic pipeline. This system enables accurate and unobtrusive real‐time motion tracking, providing a scalable, material‐based solution to ...
Jinhyeok Oh, Joonbum Bae
wiley +1 more source
Recurrent Constellations of Embryonic Malformations (RCEM): Teratogenicity Linked to Transient Hypoxia and Hormone Pregnancy Tests Agrees With RCEM and Suggest a Reactive Oxygen Species Pathogenesis. [PDF]
Adam AP +3 more
europepmc +1 more source
This study proposes a deep learning approach to evaluate the fatigue crack behavior in metals under overload conditions. Using digital image correlation to capture the strain near crack tips, convolutional neural networks classify crack states as normal, overload, or recovery, and accurately predict fatigue parameters.
Seon Du Choi +5 more
wiley +1 more source
Optimizing solar irradiance forecasting: ANN models enhanced with ADAM and Cuckoo search algorithm. [PDF]
Sadiq M +6 more
europepmc +1 more source
Correction to "Mechanistic Insights into the Electroreduction of Carbon Dioxide to Formate on Palladium". [PDF]
Winzely M +12 more
europepmc +1 more source

