On the public citation graph
Tuberculosis Detection in Chest Radiographs Using Spotted Hyena Algorithm Optimized Deep and Handcrafted Features
0 signed · 62 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
1 of the 41 references listed on this page is in the Retraction Watch database as retracted (export 2026-10-28): 10.1155/2022/7384131 (notice 2023-12-13).
Dataset join, best-effort; this page does not check the publisher record. Retraction Watch data via Crossref Labs, used with credit; OpenCitations Index (CC0) and Meta (CC BY 4.0); dataset doi:10.7910/DVN/WT8VOA (CC BY 4.0).
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-69744-0_6openalex-snapshot
An Efficient Mixture of Deep and Machine Learning Models for COVID-19 and Tuberculosis Detection Using X-Ray Images in Resource Limited Settings
inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-snapshot
U-Net: Convolutional Networks for Biomedical Image Segmentation
inferredcites →https://doi.org/10.1007/978-981-13-0761-4_81openalex-snapshot
Spotted Hyena Optimizer for Solving Complex and Non-linear Constrained Engineering Problems
inferredcites →https://doi.org/10.1007/s00604-020-04669-xopenalex-snapshot
Portable electrochemical immunosensor for detection of Mycobacterium tuberculosis secreted protein CFP10-ESAT6 in clinical sputum samples
inferredcites →https://doi.org/10.1007/s10044-020-00950-0openalex-snapshot
A novel framework for rapid diagnosis of COVID-19 on computed tomography scans
inferredcites →https://doi.org/10.1007/s10278-021-00534-2openalex-snapshot
Deep CNN with Hybrid Binary Local Search and Particle Swarm Optimizer for Exudates Classification from Fundus Images
inferredcites →https://doi.org/10.1007/s10489-020-02149-6openalex-snapshot
Densely connected convolutional networks-based COVID-19 screening model
inferredcites →https://doi.org/10.1016/j.advengsoft.2017.05.014openalex-snapshot
Spotted hyena optimizer: A novel bio-inspired based metaheuristic technique for engineering applications
inferredcites →https://doi.org/10.1016/j.bbe.2021.05.010openalex-snapshot
An automated skin melanoma detection system with melanoma-index based on entropy features
inferredcites →https://doi.org/10.1016/j.isprsjprs.2020.01.013openalex-snapshot
ResUNet-a: A deep learning framework for semantic segmentation of remotely sensed data
inferredcites →https://doi.org/10.1016/j.patrec.2019.03.027openalex-snapshot
Global weighted LBP based entropy features for the assessment of pulmonary hypertension
inferredcites →https://doi.org/10.1016/s2213-2600(19)30418-7openalex-snapshot
WHO global progress report on tuberculosis elimination
inferredcites →https://doi.org/10.1109/access.2020.2971257openalex-snapshot
Modality-Specific Deep Learning Model Ensembles Toward Improving TB Detection in Chest Radiographs
inferredcites →https://doi.org/10.1109/access.2020.3031384openalex-snapshot
Reliable Tuberculosis Detection Using Chest X-Ray With Deep Learning, Segmentation and Visualization
inferredcites →https://doi.org/10.1109/elnano.2018.8477564openalex-snapshot
Chest X-Ray Analysis of Tuberculosis by Deep Learning with Segmentation and Augmentation
inferredcites →https://doi.org/10.1109/icbme49163.2019.9030395openalex-snapshot
Feature Selection for Contour-based Tuberculosis Detection from Chest X-Ray Images
inferredcites →https://doi.org/10.1109/icbsii51839.2021.9445126openalex-snapshot
U-Net Supported Segmentation of Ischemic-Stroke-Lesion from Brain MRI Slices
inferredcites →https://doi.org/10.1109/icsipa.2017.8120663openalex-snapshot
Deep-learning: A potential method for tuberculosis detection using chest radiography
inferredcites →https://doi.org/10.1109/ict.2019.8798798openalex-snapshot
Deep Learning Models for Tuberculosis Detection from Chest X-ray Images
inferredcites →https://doi.org/10.1109/tpami.2016.2644615openalex-snapshot
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
inferredcites →https://doi.org/10.1155/2018/5078268openalex-snapshot
A Novel Feature Selection Method Based on Extreme Learning Machine and Fractional-Order Darwinian PSO
inferredcites →https://doi.org/10.1155/2020/8894694openalex-snapshot
Applications of Artificial Intelligence and Big Data Analytics in m-Health: A Healthcare System Perspective
inferredcites →https://doi.org/10.1155/2021/1972662openalex-snapshot
A Deep Learning-Based Classification Method for Different Frequency EEG Data
inferredcites →https://doi.org/10.1155/2021/2571863openalex-snapshot
Dingo Optimizer: A Nature-Inspired Metaheuristic Approach for Engineering Problems
inferredcites →https://doi.org/10.1155/2021/5527698openalex-snapshot
An Optimized Method for Skin Cancer Diagnosis Using Modified Thermal Exchange Optimization Algorithm
inferredcites →https://doi.org/10.1155/2021/6170416openalex-snapshot
Deep Learning Algorithms for Detection and Classification of Gastrointestinal Diseases
inferredcites →https://doi.org/10.1155/2021/9269173openalex-snapshot
Deep Learning Algorithm for COVID-19 Classification Using Chest X-Ray Images
inferredcites →https://doi.org/10.1155/2022/7384131openalex-snapshot
Deep Learning Model for the Automatic Classification of White Blood Cells
inferredcites →https://doi.org/10.11591/ijai.v8.i4.pp429-435openalex-snapshot
Ensemble deep learning for tuberculosis detection using chest X-ray and canny edge detected images
inferredcites →https://doi.org/10.1371/journal.pone.0243189openalex-snapshot
Real-time neural network based predictor for cov19 virus spread
inferredcites →https://doi.org/10.3233/xst-210976openalex-snapshot
Tuberculosis detection in chest X-ray using Mayfly-algorithm optimized dual-deep-learning features
inferredcites →https://doi.org/10.3233/xst-211050openalex-snapshot
Automatic detection of COVID-19 in chest radiographs using serially concatenated deep and handcrafted features
inferredcites →https://doi.org/10.32604/cmc.2021.018103openalex-snapshot
Real-Time Violent Action Recognition Using Key Frames Extraction and Deep Learning
inferredcites →https://doi.org/10.3389/frai.2022.827299openalex-snapshot
TB-Net: A Tailored, Self-Attention Deep Convolutional Neural Network Design for Detection of Tuberculosis Cases From Chest X-Ray Images
inferredcites →https://doi.org/10.3390/app10020559openalex-snapshot
A Novel Transfer Learning Based Approach for Pneumonia Detection in Chest X-ray Images
inferredcites →https://doi.org/10.3390/app10103429openalex-snapshot
A Customized VGG19 Network with Concatenation of Deep and Handcrafted Features for Brain Tumor Detection
inferredcites →https://doi.org/10.3390/diagnostics11081395openalex-snapshot
Local Pattern Transformation Based Feature Extraction for Recognition of Parkinson’s Disease Based on Gait Signals
inferredcites →https://doi.org/10.4018/ijdwm.2021040104openalex-snapshot
Development of a Framework for Preserving the Disease-Evidence-Information to Support Efficient Disease Diagnosis
inferredcites →https://doi.org/10.5755/j01.itc.50.2.28087openalex-snapshot
Convolutional-Neural-Network Assisted Segmentation and SVM Classification of Brain Tumor in Clinical MRI Slices
inferredcites →https://doi.org/10.7717/peerj-cs.456openalex-snapshot
Detection of diabetic retinopathy using a fusion of textural and ridgelet features of retinal images and sequential minimal optimization classifier
inferredcites →https://doi.org/10.7717/peerj-cs.564openalex-snapshot
Overview of current state of research on the application of artificial intelligence techniques for COVID-19
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4514518openalex-extracted
Detection of Tuberculosis Using X-Ray Images with a Hybrid Approach of Cnn and Hog
inferred← citeshttps://doi.org/10.5281/zenodo.10425810openalex-extracted
dataset- Tuberculosis detection using Squid Game Optimization with Deep Learning Model on Chest X-Ray Images
inferred← citeshttps://doi.org/10.1007/s10791-025-09791-zopenalex-snapshot
An explainable hybrid deep learning system for tuberculosis detection with Grad-CAM
inferred← citeshttps://doi.org/10.1007/s11760-023-02732-7openalex-snapshot
CLBO: chef leader-based optimization enabled deep learning for tuberculosis detection using x-ray images
inferred← citeshttps://doi.org/10.1016/j.bspc.2025.108531openalex-snapshot
Multi-task deep learning for bacilli detection and counting in sputum smear microscopy
inferred← citeshttps://doi.org/10.1016/j.imu.2025.101651openalex-snapshot
The role of machine learning in infectious disease early detection and prediction in the MENA region: A systematic review
inferred← citeshttps://doi.org/10.1016/j.procs.2023.12.057openalex-snapshot
Enhancing Tuberculosis Detection: Leveraging RF-HOG Model for Automated Diagnosis from Chest X-ray Images
inferred← citeshttps://doi.org/10.1063/5.0282765openalex-snapshot
Implementing ResNet101V2 to improve the precision during tuberculosis detection in chest X-ray compared to ResNet50
inferred← citeshttps://doi.org/10.1109/access.2024.3505608openalex-snapshot
Explainable Model of Fusion Network With Enhanced Optimization Approach for Tuberculosis Diagnosis
inferred← citeshttps://doi.org/10.1145/3596947.3596963openalex-snapshot
Framework for Healthy/Hemorrhagic Brain Condition Detection using CT Scan Images
inferred← citeshttps://doi.org/10.18280/ts.410142openalex-snapshot
Enhanced Karyotyping Through Deep Learning-Assisted Segmentation and Classification of Chromosomal Cells
inferred← citeshttps://doi.org/10.3389/fpubh.2023.1109236openalex-snapshot
A framework to distinguish healthy/cancer renal CT images using the fused deep features
inferred← citeshttps://doi.org/10.3390/economies11030090openalex-snapshot
The Role of International Research Collaboration and Faculty Related Factors in Publication Citations: Evidence from Lebanon
inferred← citeshttps://doi.org/10.3390/electronics12010113openalex-snapshot
SHO-CNN: A Metaheuristic Optimization of a Convolutional Neural Network for Multi-Label News Classification
inferred← citeshttps://doi.org/10.3390/jcm12010303openalex-snapshot
Diagnostic Accuracy of the Artificial Intelligence Methods in Medical Imaging for Pulmonary Tuberculosis: A Systematic Review and Meta-Analysis
inferred← citeshttps://doi.org/10.3390/life12111848openalex-snapshot
Automatic Detection of Tuberculosis Using VGG19 with Seagull-Algorithm
inferred← citeshttps://doi.org/10.3934/mbe.2023861openalex-snapshot
Colon histology slide classification with deep-learning framework using individual and fused features
inferred← citeshttps://doi.org/10.61466/ijcmr1030014openalex-snapshot
Deep Transfer Learning with Fused Optimal Features for Detection of Diabetic Foot Ulcers
inferred← citeshttps://doi.org/10.9781/ijimai.2023.05.004openalex-snapshot
ResNet18 Supported Inspection of Tuberculosis in Chest Radiographs With Integrated Deep, LBP, and DWT Features.
showing the first 20 of 21 · page through all 21
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.