Pathologist Validation of a Machine Learning–Derived Feature for Colon Cancer Risk Stratification
Sign Up to like & getrecommendations! Published in 2023 at "JAMA Network Open"
DOI: 10.1001/jamanetworkopen.2022.54891
Abstract: Key Points Question Can a prognostic machine learning–derived histopathologic feature be learned and validated by pathologists? Findings In this prognostic study, 2 pathologists were able to learn a machine learning–derived histopathologic feature and validate its… read more here.
Keywords: colon cancer; machine learning; feature; learning derived ... See more keywords
The prediction model of nitrogen nutrition in cotton canopy leaves based on hyperspectral visible-near infrared band feature fusion.
Sign Up to like & getrecommendations! Published in 2023 at "Biotechnology journal"
DOI: 10.1002/biot.202200623
Abstract: Hyperspectral remote sensing technology is becoming increasingly popular in various fields due to its ability to provide detailed information about crop growth and nutritional status. The use of hyperspectral technology to predict SPAD (Soil and… read more here.
Keywords: nitrogen nutrition; cotton canopy; feature;
Improving Harris hawks optimization algorithm for hyperparameters estimation and feature selection in v‐support vector regression based on opposition‐based learning
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Chemometrics"
DOI: 10.1002/cem.3311
Abstract: Many real problems have been solved by support vector regression, especially v‐support vector regression (v‐SVR), but there are hyperparameters that usually needed to tune. In addition, v‐SVR cannot perform feature selection. Nature‐inspired algorithms have been… read more here.
Keywords: vector regression; feature; feature selection; support vector ... See more keywords
Computer‐aided diagnosis of retinal diseases using multidomain feature fusion
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22379
Abstract: In this article, an attempt is made to combine both transform and spatial domain features to increase the accuracy, sensitivity, and specificity for the classification of retinal diseases. Papilloedema, macular edema, glaucoma, diabetic retinopathy (DR),… read more here.
Keywords: feature; feature fusion; fusion; computer aided ... See more keywords
Thermal imaging method to evaluate childhood obesity based on machine learning techniques
Sign Up to like & getrecommendations! Published in 2021 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22572
Abstract: The purposes of the study were (i) to determine the potential of thermal imaging to assess the difference in the thermal pattern in various body regions of studied population; (ii) to compare the performance of… read more here.
Keywords: machine learning; feature; thermal imaging; method ... See more keywords
BDU‐net: Toward accurate segmentation of dental image using border guidance and feature map distortion
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22704
Abstract: The importance of instance segmentation for each tooth is increasing in dental disease diagnosis and computer‐assisted treatment. However, most existing segmentation methods are mainly concerned with semantic feature extraction, while ignoring complex situations such as… read more here.
Keywords: border guidance; guidance feature; feature map; feature ... See more keywords
Deep learning and machine learning‐based early survival predictions of glioblastoma patients using pre‐operative three‐dimensional brain magnetic resonance imaging modalities
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22804
Abstract: To propose and implement an automated machine learning (ML) based methodology to predict the overall survival of glioblastoma multiforme (GBM) patients. In the proposed methodology, we used deep learning (DL) based 3D U‐shaped Convolutional Neural… read more here.
Keywords: methodology; machine learning; feature; brain ... See more keywords
Optimal channel and frequency band‐based feature selection for motor imagery electroencephalogram classification
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22823
Abstract: Common spatial pattern (CSP) is a widely adopted method for electroencephalogram (EEG) feature extraction in brain‐computer interface (BCI) based on motor imagery. Bandpass‐filtering EEG into several subbands related to brain activity tasks is an effective… read more here.
Keywords: optimal channel; feature; channel frequency; feature selection ... See more keywords
An automatic gastric polyp detection technique using deep learning
Sign Up to like & getrecommendations! Published in 2023 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22850
Abstract: Over the last few years, researchers have focused on computer‐aided polyp detection in gastroscopy. Deep learning (DL) has shown great promise for polyps' identification. The most exceptional contribution of DL methods in gastroenterology is their… read more here.
Keywords: map; polyp detection; feature; detection ... See more keywords
HFENet: A lightweight hand‐crafted feature enhanced CNN for ceramic tile surface defect detection
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22935
Abstract: Inkjet printing technology can make tiles with very rich and realistic patterns, so it is widely adopted in the ceramic industry. However, the frequent nozzle blockage and inconsistent inkjet volume by inkjet printing devices, usually… read more here.
Keywords: tile surface; detection; hand crafted; feature ... See more keywords
IoT botnet detection with feature reconstruction and interval optimization
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.23074
Abstract: The existing botnet detection methods have the problems of uneven sampling, poor feature selection, and weak generalization ability, resulting in low detection and classification results and poor adaptability to the internet of things (IoT) environment… read more here.
Keywords: interval optimization; feature; detection; feature reconstruction ... See more keywords