Results 161 to 170 of about 7,794,647 (291)

Comparing the Performances of Support Vector Machines and Artificial Neural Networks for Predicting Coronary Artery Diseases: A Cross-Sectional Study. [PDF]

Cardiol Res Pract
Shariatnia S, Rajabi A, Ziaratban M, Salehi A, Vakili M.   +4 more
europepmc   +1 more source

Lignin Mimicking Protein Methylation Augments the Efficacy of FOLFOX Chemotherapy by Anchoring Thymidylate Synthase

Advanced Materials, EarlyView.
Lignin‐mimicking protein methylation can enhance the efficacy and mitigate the toxicity of the classic FOLFOX chemotherapy regimen. ABSTRACT FOLFOX has served as the standard chemotherapy regimen for advanced stages, specifically in the treatment of pancreatic, colorectal, and bladder cancers.
Shiyao Song, Yan‐Lai Tang, Xiaoting Liu, Jiayi Zheng, Chong Wu, Tang Li, Junhong Ye, Dianmin Xia, Yong Mei, Jingxuan Ma, Libin Huang, Xuequn Luo, Liheng Chen, Yanlin Qin, Weiling He   +14 more
wiley   +1 more source

Prediction model for frailty risk in ischemic stroke patients: Application and validation of support vector machines and nomograms. [PDF]

Medicine (Baltimore)
Kang YL, Kong JT, Tian H.
europepmc   +1 more source

Deep learning and support vector machines for transcription start site identification. [PDF]

PeerJ Comput Sci, 2023
Barbero-Aparicio JA, Olivares-Gil A, Díez-Pastor JF, García-Osorio C.   +3 more
europepmc   +1 more source

LEAD: Literature Enhanced Ab Initio Discovery of Nitride Dusting Layers for Enhanced Tunnel Magnetoresistance and Lower Resistance Magnetic Tunnel Junctions

Advanced Materials, EarlyView.
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam, William S. Rogers, Chen‐Yu Hu, Ming‐Yuan Song, Xinyu Bao, Shehrin Sayed, Jean Anne C. Incorvia   +6 more
wiley   +1 more source

PET-TURTLE: Deep Unsupervised Support Vector Machines for Imbalanced Data Clusters. [PDF]

IEEE Signal Process Lett
Salazar Cavazos J.
europepmc   +1 more source

Retracted: Design of a Regional Economic Forecasting Model Using Optimal Nonlinear Support Vector Machines. [PDF]

Comput Intell Neurosci, 2023
Neuroscience CIA.
europepmc   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

Driver Fatigue Detection using EEG Microstate Features and Support Vector Machines. [PDF]

J Biomed Phys Eng
Yaddasht Z, Kazemi K, Danyali H, Aarabi A.   +3 more
europepmc   +1 more source

Azobenzene's Cross‐Scale Optics and Photonics: Molecular Photoswitching, Mesoscopic Material Motions, and Adaptive Devices

Advanced Materials, EarlyView.
Azobenzene photoswitches translate molecular‐scale E/Z photoisomerization into macroscopic material responses and device‐level photonic functions. This Review highlights how azobenzene research has evolved from molecular photochemistry to photoalignment, mass migration, photomechanics, and heat release, ultimately enabling holography, reconfigurable ...
Heeju Son, Soyul Kwak, Heerin Noh, Minsang Kim, Doyeon Noh, Subhayan Chakraborty, Jaewon Lee, YongDeok Cho, Kyeongsoo Kim, Taewoong Eom, Moonyoung Kim, Jangwon Kim, Hoyoung Lee, Soyoung Lee, Jaehun Kim, Grace G. D. Han, Shin‐Tson Wu, Stefano Oscurato, Arri Priimagi, Marina Saphiannikova, Seungwoo Lee   +20 more
wiley   +1 more source