Results 151 to 160 of about 937,595 (329)
Support vector machines with selective kernel scaling for protein classification and identification of key amino acid positions [PDF]
, 2002 Nela Zavaljevski +2 more
openalex +1 more source
Advanced Functional Materials, EarlyView.This study introduces a self‐powered real‐time ionic TENG temperature sensing system for flexible thermal management with high and real‐time temperature monitoring. Ionic liquids and elastomer chains are investigated under temperature via electrochemical and physical analysis, resulting in enhancing thermal sensitivity and output performance on TENG ...
Hee Jae Hwang +9 more
wiley +1 more source
Identifying genes related to drug anticancer mechanisms using support vector machine [PDF]
, 2002 Lei Bao, Zhirong Sun
openalex +1 more source
Transducer Materials Mediated Deep Brain Stimulation in Neurological Disorders
Advanced Functional Materials, EarlyView.This review discusses advanced transducer materials for improving deep brain stimulation (DBS) in neurological disorders. These materials respond to light, ultrasound, or magnetic fields, enabling precise, less invasive neuromodulation. Their stimulus‐responsive properties enhance neural control and adaptive therapy, paving the way for next‐generation ...
Di Zhao +5 more
wiley +1 more source
Part of Speech Tagging in Thai Language Using Support Vector Machine
, 2001 Masaki Murata, Qing Ma, Hitoshi Isahara
openalex +2 more sources
Machine Learning Guided Design of Nerve‐On‐A‐Chip Platforms with Promoted Neurite Outgrowth
Advanced Functional Materials, EarlyView.Compared to labor‐intensive trial‐and‐error experimentation, a machine learning (ML)‐guided workflow, incorporating cell viability assays, data augmentation, ensemble modeling, and model interpretation, is developed to accelerate nerve‐on‐a‐chip optimization and uncover data‐driven design principles.
Tsai‐Chun Chung +8 more
wiley +1 more source
Advanced Materials Interfaces, EarlyView., 2023 This review discusses the use of Surface‐Enhanced Raman Spectroscopy (SERS) combined with Artificial Intelligence (AI) for detecting antimicrobial resistance (AMR). Various SERS studies used with AI techniques, including machine learning and deep learning, are analyzed for their advantages and limitations.
Zakarya Al‐Shaebi +4 more
wiley +1 more source
A System Identification Method for Linear Regression Models Based on Support Vector Machine
, 2001 Shuichi Adachi +2 more
openalex +2 more sources
Incorporating Invariances in Nonlinear Support Vector Machines [PDF]
, 2002 Olivier Chapelle, Bernhard Schölkopf
openalex +1 more source