Results 151 to 160 of about 427,183 (276)

Transfer learning models for bacterial strain dissemination biomarkers using weighted non-parallel proximal support vector machines. [PDF]

BMC Bioinformatics
Ugwu UO, Slayden RA, Kirby M.
europepmc   +1 more source

High‐Performance Transparent, Deformable, and Recoverable Biomimetic Stevia–PVA Hydrogel Triboelectric Nanogenerator with Machine Learning‐Assisted Motion Recognition

Advanced Materials, EarlyView.
A transparent, deformable stevia–PVA hydrogel triboelectric nanogenerator delivers significantly enhanced mechanical strength and electrical output through biomimetic hydrogen‐bonded networks. Coupled with machine learning–assisted signal recognition, the self‐powered hydrogel enables accurate human‐motion sensing for intelligent wearable and IoT ...
Thien Trung Luu, Bui Minh Quang, Toan Minh Pham, Jinsoo Kim, Kyungwho Choi, Dukhyun Choi   +5 more
wiley   +1 more source

Support vector machines predict postoperative memory outcomes in temporal lobe epilepsies. [PDF]

Epilepsia Open
Ethofer S, Erb M, Milian M, Rona S, Lerche H, Honegger J, Ethofer T.   +6 more
europepmc   +1 more source

Radiomics Signature Based on Support Vector Machines for the Prediction of Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer. [PDF]

Cancers (Basel), 2023
Li C, Chen H, Zhang B, Fang Y, Sun W, Wu D, Su Z, Shen L, Wei Q.   +8 more
europepmc   +1 more source

Advanced Design for Weakly Coupled Resonators by Automatic Active Optimization

Advanced Materials Technologies, EarlyView.
An Automatic Active Optimization (AAO) strategy integrates machine learning predictors and genetic algorithms in a closed‐loop workflow. By iteratively expanding its dataset with new discoveries, AAO overcomes the limits of conventional methods. This approach finds superior microstructural designs beyond the initial sample space. We demonstrate this on
Wei Yue, Yuan Gao, Fanping Sui, Jason Wang, Megan Teng, Peggy Tsao, Huicong Deng, Yande Peng, Liwei Lin   +8 more
wiley   +1 more source

Support Vector Machines in Polymer Science: A Review. [PDF]

Polymers (Basel)
Malashin I, Tynchenko V, Gantimurov A, Nelyub V, Borodulin A.   +4 more
europepmc   +1 more source

Flow‐Adaptive Gas Sensing Enabled Using a Uniform Au Nanosheet Sensor Array and a Neural Network Inference

Advanced Materials Technologies, EarlyView.
Integrated Au nanosheet sensor array enables simultaneous inference of gas concentration and flow rate via deep neural network analysis, without external flow control. ABSTRACT Gas sensor responses are considerably affected by gas flow rates, thereby inhibiting the accurate detection of target gas concentrations in variable‐flow applications such as ...
Taro Kato, Takahisa Tanaka, Yusuke Hamanaka, Ryo Toyoshima, Ken Uchida   +4 more
wiley   +1 more source

Classification of Speech and Associated EEG Responses from Normal-Hearing and Cochlear Implant Talkers Using Support Vector Machines. [PDF]

Audiol Res
Raghavendra S, Lee S, Tan CT.
europepmc   +1 more source

Churn prediction in telecommunication industry using kernel Support Vector Machines. [PDF]

PLoS One, 2022
Y NN, Ly TV, Son DVT.
europepmc   +1 more source

End‐to‐End Sensing Systems for Breast Cancer: From Wearables for Early Detection to Lab‐Based Diagnosis Chips

Advanced Materials Technologies, EarlyView.
This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane, Lyn I. Jones, Richard M. Martin, Helen Winter, Faezeh Arab Hassani   +4 more
wiley   +1 more source