KDSAE: Chronic kidney disease classification with multimedia data learning using deep stacked autoencoder network
Sign Up to like & getrecommendations! Published in 2019 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-019-07839-z
Abstract: In recent times, Chronic Kidney Disease (CKD) has affected more than 10% of the population worldwide and millions of people die every year. So, early-stage detection of CKD could be beneficial for increasing the life… read more here.
Keywords: disease classification; kidney disease; disease; chronic kidney ... See more keywords
Glomerular Disease Classification and Lesion Identification by Machine Learning.
Sign Up to like & getrecommendations! Published in 2021 at "Biomedical journal"
DOI: 10.1016/j.bj.2021.08.011
Abstract: BACKGROUND Classification of glomerular diseases and identification of glomerular lesions require careful morphological examination by experienced nephropathologists, which is labor-intensive, time-consuming, and prone to interobserver variability. In this regard, recent advance in machine learning-based image… read more here.
Keywords: classification; machine learning; lesion identification; model ... See more keywords
Multiclass Disease Classification from Microbial Whole-Community Metagenomes
Sign Up to like & getrecommendations! Published in 2020 at "Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing"
DOI: 10.1101/726901
Abstract: There is a wealth of information contained within one’s microbiome regarding their physiology and environment, and this is a promising avenue for developing non-invasive diagnostic tools. Here, we utilize 5643 aggregated, annotated whole-community metagenomes from… read more here.
Keywords: disease; community metagenomes; multiclass disease; disease classification ... See more keywords
Thorax Disease Classification Based on Pyramidal Convolution Shuffle Attention Neural Network
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3198958
Abstract: Chest X-ray is one of the most common radiological examinations for screening thoracic diseases. Despite the existing methods based on convolution neural network that have achieved remarkable progress in thoracic disease classification from chest X-ray… read more here.
Keywords: disease classification; pyramidal convolution; shuffle attention; convolution ... See more keywords
Disease Classification Model Based on Multi-Modal Feature Fusion
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3252011
Abstract: Aiming at the application of classification tasks in deep learning in disease classification, this paper proposes a disease classification model based on multi-modal feature fusion. In this model, chest X-ray images of patients are used… read more here.
Keywords: classification; feature fusion; multi modal; model ... See more keywords
Convolutional Neural Network with Graphical Lasso to Extract Sparse Topological Features for Brain Disease Classification.
Sign Up to like & getrecommendations! Published in 2020 at "IEEE/ACM transactions on computational biology and bioinformatics"
DOI: 10.1109/tcbb.2020.2989315
Abstract: The functional connectivity provides new insights into the mechanisms of the human brain at network-level, which has been proved to be an effective biomarker for brain disease classification. Recently, machine learning methods have played an… read more here.
Keywords: network; disease classification; brain disease; topological features ... See more keywords
Of Registries and Disease Classification: Unmasking the Challenges of Pediatric Pulmonary Hypertension
Sign Up to like & getrecommendations! Published in 2022 at "American Journal of Respiratory and Critical Care Medicine"
DOI: 10.1164/rccm.202206-1180ed
Abstract: direct and epigenetic consequences of exposure that may impact large populations in both the short and long term (11). Planning ahead to understand how exposures cause disease will be critical, and, ideally, such knowledge would… read more here.
Keywords: registries disease; challenges pediatric; classification unmasking; respiratory ... See more keywords
Rational selection of RGB channels for disease classification based on IPPG technology.
Sign Up to like & getrecommendations! Published in 2022 at "Biomedical optics express"
DOI: 10.1364/boe.451736
Abstract: The green channel is usually selected as the optimal channel for vital signs monitoring in image photoplethysmography (IPPG) technology. However, some controversies arising from the different penetrability of skin tissue in visible light remain unresolved,… read more here.
Keywords: classification; ippg technology; rgb channels; channel ... See more keywords
Lung Disease Classification using GLCM and Deep Features from Different Deep Learning Architectures with Principal Component Analysis
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Integrated Engineering"
DOI: 10.30880/ijie.2018.10.07.008
Abstract: Lung disease classification is an important stage in implementing a Computer Aided Diagnosis (CADx) system. CADx systems can aid doctors as a second rater to increase diagnostic accuracy for medical applications. It has also potential… read more here.
Keywords: classification; disease classification; lung disease; deep features ... See more keywords
MLFAnet: A Tomato Disease Classification Method Focusing on OOD Generalization
Sign Up to like & getrecommendations! Published in 2023 at "Agriculture"
DOI: 10.3390/agriculture13061140
Abstract: Tomato disease classification based on images of leaves has received wide attention recently. As one of the best tomato disease classification methods, the convolutional neural network (CNN) has an immense impact due to its impressive… read more here.
Keywords: disease; method; tomato disease; disease classification ... See more keywords
A Study on Multiple Factors Affecting the Accuracy of Multiclass Skin Disease Classification
Sign Up to like & getrecommendations! Published in 2021 at "Applied Sciences"
DOI: 10.3390/app11177929
Abstract: Diagnosis of skin diseases by human experts is a laborious task prone to subjective judgment. Aided by computer technology and machine learning, it is possible to improve the efficiency and robustness of skin disease classification.… read more here.
Keywords: classification; disease classification; accuracy; skin disease ... See more keywords