Segmentation, feature extraction and classification of leukocytes leveraging neural networks, a comparative study
Sign Up to like & getrecommendations! Published in 2024 at "Cytometry Part A"
DOI: 10.1002/cyto.a.24832
Abstract: The gold standard of leukocyte differentiation is a manual examination of blood smears, which is not only time and labor intensive but also susceptible to human error. As to automatic classification, there is still no… read more here.
Keywords: classification; deep learning; segmentation; feature extraction ... See more keywords
Efficient spine segmentation network based on multi‐scale feature extraction and multi‐dimensional spatial attention
Sign Up to like & getrecommendations! Published in 2024 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.23046
Abstract: In spine imaging, efficient automatic segmentation is crucial for clinical decision‐making, yet current models increase accuracy at the expense of elevated parameter counts and computational complexity, complicating integration with contemporary medical devices. Addressing identified challenges,… read more here.
Keywords: segmentation; attention; feature extraction; spine segmentation ... See more keywords
Efficient feature extraction and hybrid deep learning for early identification of uterine fibroids in ultrasound images
Sign Up to like & getrecommendations! Published in 2024 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.23073
Abstract: Non‐cancerous growths called uterine fibroids develop in the uterus. They can vary in size, location, and number, and can produce symptoms including excessive menstrual flow, pelvic discomfort, and reproductive problems. Early detection of uterine fibroids… read more here.
Keywords: detection; feature extraction; uterine fibroids; ultrasound images ... See more keywords
Privacy‐preserving CNN feature extraction and retrieval over medical images
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22991
Abstract: Online medicine diagnosis based on pathological images has been regarded as a pervasive method due to the advances in electronic healthcare and Internet of Things (IoT), however, it also causes storage and computing stress on… read more here.
Keywords: retrieval; privacy; privacy preserving; feature extraction ... See more keywords
MSCMLCIDTI: Drug–Target Interaction Prediction Based on Multiscale Feature Extraction and Deep Interactive Attention Fusion Mechanisms
Sign Up to like & getrecommendations! Published in 2025 at "Journal of Computational Chemistry"
DOI: 10.1002/jcc.70170
Abstract: Drug–target interaction prediction serves as a crucial component in accelerating drug discovery. To overcome current limitations in deep learning approaches, specifically the inadequate representation of local features and insufficient modeling of drug and target information… read more here.
Keywords: interaction; drug; drug target; feature extraction ... See more keywords
Hybrid feature extraction techniques for microscopic hepatic fibrosis classification
Sign Up to like & getrecommendations! Published in 2018 at "Microscopy Research and Technique"
DOI: 10.1002/jemt.22985
Abstract: Chronic liver diseases' hallmark is the fibrosis that results in liver function failure in advanced stages. One of the serious parasitic diseases affecting the liver tissues is schistosomiasis. Immunologic reactions to Schistosoma eggs leads to… read more here.
Keywords: hybrid feature; classification; fibrosis; liver diseases ... See more keywords
Consensus-based feature extraction in rs-fMRI data analysis
Sign Up to like & getrecommendations! Published in 2018 at "Soft Computing"
DOI: 10.1007/s00500-017-2596-5
Abstract: The high-dimensional nature of resting state functional MRI (fMRI) data implies the need of suitable feature selection techniques. Traditional univariate techniques are fast and straightforward to interpret, but are unable to unveil relationships among multiple… read more here.
Keywords: fmri; fmri data; data analysis; consensus ... See more keywords
Semi-supervised fuzzy neighborhood preserving analysis for feature extraction in hyperspectral remote sensing images
Sign Up to like & getrecommendations! Published in 2017 at "Neural Computing and Applications"
DOI: 10.1007/s00521-017-3279-y
Abstract: Semi-supervised feature extraction methods are an important focus of interest in data mining and machine learning areas. These methods are improved methods based on learning from a combination of labeled and unlabeled data. In this… read more here.
Keywords: semi supervised; method; remote sensing; feature extraction ... See more keywords
Iris tissue recognition based on GLDM feature extraction and hybrid MLPNN-ICA classifier
Sign Up to like & getrecommendations! Published in 2018 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3754-0
Abstract: The use of iris tissue for identification is an accurate and reliable system for identifying people. This method consists of four main processing stages, namely segmentation, normalization, feature extraction, and matching. In this study, a… read more here.
Keywords: hybrid mlpnn; feature; iris tissue; feature extraction ... See more keywords
Novel system in vitro of classifying oral carcinogenesis based on feature extraction for gray-level co-occurrence matrix using scanned laser pico projector
Sign Up to like & getrecommendations! Published in 2021 at "Lasers in Medical Science"
DOI: 10.1007/s10103-020-03215-8
Abstract: Oral cancer is among the top 10 causes of death due to cancer worldwide. The prognosis for oral cancer patients is not good, with a 5-year survival rate of only 50%. Earlier and more precise… read more here.
Keywords: system; carcinogenesis; gray level; cancer ... See more keywords
A survey on feature extraction and learning techniques for link prediction in homogeneous and heterogeneous complex networks
Sign Up to like & getrecommendations! Published in 2024 at "Artificial Intelligence Review"
DOI: 10.1007/s10462-024-10998-7
Abstract: Complex networks are commonly observed in several real-world areas, such as social, biological, and technical systems, where they exhibit complicated patterns of connectedness and organised clusters. These networks have intricate topological characteristics that frequently elude… read more here.
Keywords: complex networks; feature extraction; prediction; network ... See more keywords