AutoPVS1: An automatic classification tool for PVS1 interpretation of null variants
Sign Up to like & getrecommendations! Published in 2020 at "Human Mutation"
DOI: 10.1002/humu.24051
Abstract: Null variants are prevalent within the human genome, and their accurate interpretation is critical for clinical management. In 2018, the ClinGen Sequence Variant Interpretation (SVI) Working Group refined the only criterion with a very strong… read more here.
Keywords: automatic classification; interpretation; pvs1; null variants ... See more keywords
Automatic Classification of Hepatic Cystic Echinococcosis Using Ultrasound Images and Deep Learning
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Ultrasound in Medicine"
DOI: 10.1002/jum.15691
Abstract: Hepatic cystic echinococcosis is the main form of hepatic echinococcosis, which is a life‐threatening liver disease caused by parasites that requires a precise diagnosis and proper treatment. read more here.
Keywords: cystic echinococcosis; automatic classification; echinococcosis; classification hepatic ... See more keywords
Automatic classification of informative laryngoscopic images using deep learning
Sign Up to like & getrecommendations! Published in 2022 at "Laryngoscope Investigative Otolaryngology"
DOI: 10.1002/lio2.754
Abstract: This study aims to develop and validate a convolutional neural network (CNN)‐based algorithm for automatic selection of informative frames in flexible laryngoscopic videos. The classifier has the potential to aid in the development of computer‐aided… read more here.
Keywords: informative laryngoscopic; laryngoscopic; laryngoscopic images; images using ... See more keywords
Automatic Classification of Cardiac Arrhythmias Based on Hybrid Features and Decision Tree Algorithm
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Automation and Computing"
DOI: 10.1007/s11633-019-1219-2
Abstract: Accurate classification of cardiac arrhythmias is a crucial task because of the non-stationary nature of electrocardiogram (ECG) signals. In a life-threatening situation, an automated system is necessary for early detection of beat abnormalities in order… read more here.
Keywords: decision; automatic classification; cardiac arrhythmias; classification cardiac ... See more keywords
Development of deep learning architecture for automatic classification of outdoor mobile LiDAR data
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Remote Sensing"
DOI: 10.1080/01431161.2018.1547929
Abstract: ABSTRACT This paper proposes a deep convolutional neural network (CNN) architecture for automatic classification of mobile laser scanning (MLS) data obtained for outdoor environment, which are characterized by noise, clutter, large size and larger quantum… read more here.
Keywords: automatic classification; classification; electric pole; architecture automatic ... See more keywords
A framework for automatic classification of mobile LiDAR data using multiple regions and 3D CNN architecture
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Remote Sensing"
DOI: 10.1080/01431161.2020.1734252
Abstract: ABSTRACT This paper proposes a framework for automatic classification of mobile laser scanner (MLS) point cloud using multi-faceted multi-object convolutional neural network (MMCN). The proposed method takes a full three-dimensional (3D) point cloud as input… read more here.
Keywords: automatic classification; framework automatic; classification; framework ... See more keywords
Automatic Classification of Slit-Lamp Photographs by Imaging Illumination.
Sign Up to like & getrecommendations! Published in 2023 at "Cornea"
DOI: 10.1097/ico.0000000000003318
Abstract: PURPOSE The aim of this study was to facilitate deep learning systems in image annotations for diagnosing keratitis type by developing an automated algorithm to classify slit-lamp photographs (SLPs) based on illumination technique. METHODS SLPs… read more here.
Keywords: photographs; slit lamp; slit beam; automatic classification ... See more keywords
A novel automatic classification system based on hybrid unsupervised and supervised machine learning for electrospun nanofibers
Sign Up to like & getrecommendations! Published in 2021 at "IEEE/CAA Journal of Automatica Sinica"
DOI: 10.1109/jas.2020.1003387
Abstract: The manufacturing of nanomaterials by the electrospinning process requires accurate and meticulous inspection of related scanning electron microscope ( SEM ) images of the electrospun nanofiber, to ensure that no structural defects are produced. The… read more here.
Keywords: system; classification system; automatic classification; novel automatic ... See more keywords
Deep Convolutional Neural Networks for Feature-Less Automatic Classification of Independent Components in Multi-Channel Electrophysiological Brain Recordings
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Biomedical Engineering"
DOI: 10.1109/tbme.2018.2889512
Abstract: Objective: Interpretation of the electroencephalographic (EEG) and magnetoencephalographic (MEG) signals requires off-line artifacts removal. Since artifacts share frequencies with brain activity, filtering is insufficient. Blind source separation, mainly through independent component analysis (ICA), is the… read more here.
Keywords: automatic classification; eeg meg; multi channel; classification ... See more keywords
Automatic classification of major depression disorder using arterial spin labeling MRI perfusion measurements
Sign Up to like & getrecommendations! Published in 2019 at "Psychiatry and Clinical Neurosciences"
DOI: 10.1111/pcn.12862
Abstract: Neuroimaging‐based multivariate pattern‐recognition methods have been successfully used to develop diagnostic algorithms to distinguish patients with major depressive disorder (MDD) from healthy controls (HC). We developed and evaluated the accuracy of a multivariate classification method… read more here.
Keywords: arterial spin; automatic classification; spin labeling; disorder ... See more keywords
Precise automatic classification of 46 different pollen types with convolutional neural networks
Sign Up to like & getrecommendations! Published in 2020 at "PLoS ONE"
DOI: 10.1371/journal.pone.0229751
Abstract: In palynology, the visual classification of pollen grains from different species is a hard task which is usually tackled by human operators using microscopes. Many industries, including medical and pharmaceutical, rely on the accuracy of… read more here.
Keywords: automatic classification; classification; classification different; pollen grains ... See more keywords