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Explainable AI for Medical Data: Current Methods, Limitations, and Future Directions
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inferredcites →https://doi.org/10.1016/j.inffus.2021.11.008openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.jocn.2019.05.019openalex-snapshot
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Interpretation and visualization techniques for deep learning models in medical imaging
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inferredcites →https://doi.org/10.1109/cvpr.1993.341010openalex-snapshot
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inferredcites →https://doi.org/10.1109/cvpr.2015.7299087openalex-snapshot
CIDEr: Consensus-based image description evaluation
inferredcites →https://doi.org/10.1109/cvpr.2016.319openalex-snapshot
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inferredcites →https://doi.org/10.1109/iccv.2017.244openalex-snapshot
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inferredcites →https://doi.org/10.1109/iccv.2017.74openalex-snapshot
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
inferredcites →https://doi.org/10.1109/iccv.2019.00505openalex-snapshot
XRAI: Better Attributions Through Regions
inferredcites →https://doi.org/10.1109/icdm.2019.00036openalex-snapshot
Efficient Data Representation by Selecting Prototypes with Importance Weights
inferredcites →https://doi.org/10.1109/icdm.2019.00083openalex-snapshot
Automatic Generation of Medical Imaging Diagnostic Report with Hierarchical Recurrent Neural Network
inferredcites →https://doi.org/10.1109/icip40778.2020.9190952openalex-snapshot
SIDU: Similarity Difference And Uniqueness Method for Explainable AI
inferredcites →https://doi.org/10.1109/isbi.2018.8363765openalex-snapshot
Joint learning for pulmonary nodule segmentation, attributes and malignancy prediction
inferredcites →https://doi.org/10.1109/isbi45749.2020openalex-snapshot
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)
inferredcites →https://doi.org/10.1109/jbhi.2019.2944977openalex-snapshot
Computer-Aided Diagnosis in Histopathological Images of the Endometrium Using a Convolutional Neural Network and Attention Mechanisms
inferredcites →https://doi.org/10.1109/jbhi.2019.2949075openalex-snapshot
Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis
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inferredcites →https://doi.org/10.1109/jbhi.2020.3027910openalex-snapshot
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inferredcites →https://doi.org/10.1109/mc.2021.3092610openalex-snapshot
Toward Human–AI Interfaces to Support Explainability and Causability in Medical AI
inferredcites →https://doi.org/10.1109/mis.2019.2957223openalex-snapshot
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inferredcites →https://doi.org/10.1109/tbme.2020.3043215openalex-snapshot
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inferredcites →https://doi.org/10.1109/tcyb.2021.3069920openalex-snapshot
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inferredcites →https://doi.org/10.1109/tim.2021.3107056openalex-snapshot
Alzheimer’s Patient Analysis Using Image and Gene Expression Data and Explainable-AI to Present Associated Genes
inferredcites →https://doi.org/10.1109/tnnls.2016.2599820openalex-snapshot
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A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI
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RuleMatrix: Visualizing and Understanding Classifiers with Rules
inferredcites →https://doi.org/10.1109/tvcg.2018.2865027openalex-snapshot
RetainVis: Visual Analytics with Interpretable and Interactive Recurrent Neural Networks on Electronic Medical Records
inferredcites →https://doi.org/10.1145/3318464openalex-snapshot
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inferredcites →https://doi.org/10.1145/3318464.3389720openalex-snapshot
TRACER: A Framework for Facilitating Accurate and Interpretable Analytics for High Stakes Applications
inferredcites →https://doi.org/10.1145/3351095.3372850openalex-snapshot
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inferredcites →https://doi.org/10.1145/3394171.3413557openalex-snapshot
Concept-based Explanation for Fine-grained Images and Its Application in Infectious Keratitis Classification
inferredcites →https://doi.org/10.1145/3412841openalex-snapshot
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inferredcites →https://doi.org/10.1145/3418094.3418096openalex-snapshot
Covid-19 Chest Radiography Images Analysis Based on Integration of Image Preprocess, Guided Grad-CAM, Machine Learning and Risk Management
inferredcites →https://doi.org/10.1145/3514094.3534148openalex-snapshot
DIME: Fine-grained Interpretations of Multimodal Models via Disentangled Local Explanations
inferredcites →https://doi.org/10.1145/3531146.3533112openalex-snapshot
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Explainable AI (XAI): Core Ideas, Techniques, and Solutions
inferredcites →https://doi.org/10.1145/3563691openalex-snapshot
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inferredcites →https://doi.org/10.1148/radiol.2018180887openalex-snapshot
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inferredcites →https://doi.org/10.1148/radiol.2018181422openalex-snapshot
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Interpretable time-aware and co-occurrence-aware network for medical prediction
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inferredcites →https://doi.org/10.48550/arxiv.2004.01254openalex-snapshot
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inferredcites →https://doi.org/10.48550/arxiv.2004.13912openalex-snapshot
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inferredcites →https://doi.org/10.48550/arxiv.2006.00093openalex-snapshot
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inferredcites →https://doi.org/10.48550/arxiv.2006.08287openalex-snapshot
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inferredcites →https://doi.org/10.48550/arxiv.2006.11371openalex-snapshot
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inferredcites →https://doi.org/10.48550/arxiv.2101.07563openalex-snapshot
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inferredcites →https://doi.org/10.48550/arxiv.2103.13677openalex-snapshot
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inferredcites →https://doi.org/10.48550/arxiv.2107.09145openalex-snapshot
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inferredcites →https://doi.org/10.7326/0003-4819-151-4-200908180-00135openalex-snapshot
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/9781394302444.ch5openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/widm.70120openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-91379-2_4openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-94386-7_3openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-05162-2_21openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-05169-1_23openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-15092-9_2openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-30982-2_23openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-032-38939-8_11openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-95-3811-9_12openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-95-6304-3_1openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-95-7425-4_37openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s00424-025-03067-7openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10439-026-04241-3openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10462-025-11342-3openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10586-026-06087-9openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10791-026-10209-7openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11571-025-10343-wopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11948-024-00501-4openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s42979-026-05358-xopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s44163-026-01572-xopenalex-snapshot
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inferred← citeshttps://doi.org/10.1016/b978-0-443-44570-5.00002-1openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.artmed.2025.103243openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.asoc.2026.114973openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.bar.2025.101650openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.bspc.2026.110989openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.csbj.2024.08.005openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.ejrai.2025.100069openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.health.2026.100461openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.inffus.2025.103217openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.inffus.2025.103455openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jacadv.2026.102864openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.media.2026.104159openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.mlwa.2026.101000openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.mmr.2026.100012openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.neuri.2025.100215openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.patrec.2025.11.030openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.procs.2026.03.100openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.socscimed.2026.119036openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.xinn.2026.101271openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/acsami.5c14054openalex-snapshot
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inferred← citeshttps://doi.org/10.1038/s41598-025-22338-yopenalex-snapshot
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inferred← citeshttps://doi.org/10.1038/s41598-026-59740-zopenalex-snapshot
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inferred← citeshttps://doi.org/10.1080/10447318.2026.2638556openalex-snapshot
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inferred← citeshttps://doi.org/10.1080/17483107.2025.2507684openalex-snapshot
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inferred← citeshttps://doi.org/10.1093/humrep/deaf136openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/access.2025.3555543openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/access.2025.3611818openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/access.2026.3692114openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/acdsa67686.2026.11467989openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/aiei69164.2026.11497297openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/bigdata62323.2024.10826117openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/cbms61543.2024.00044openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/embc53108.2024.10782892openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/fuzz69877.2026.11626386openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/ised67359.2025.11404905openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/tce.2026.3667507openalex-snapshot
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inferred← citeshttps://doi.org/10.1111/ocr.70180openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3788112.3788141openalex-snapshot
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inferred← citeshttps://doi.org/10.1145/3816992openalex-snapshot
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inferred← citeshttps://doi.org/10.1155/crp/9055855openalex-snapshot
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inferred← citeshttps://doi.org/10.1177/20552076261462654openalex-snapshot
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inferred← citeshttps://doi.org/10.1186/s12913-026-14851-1openalex-snapshot
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inferred← citeshttps://doi.org/10.1371/journal.pone.0348508openalex-snapshot
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inferred← citeshttps://doi.org/10.1371/journal.pone.0351473openalex-snapshot
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inferred← citeshttps://doi.org/10.2139/ssrn.5421583openalex-snapshot
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inferred← citeshttps://doi.org/10.2196/95090openalex-snapshot
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inferred← citeshttps://doi.org/10.2196/preprints.91597openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fdgth.2024.1456911openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fdgth.2026.1805107openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fmed.2025.1698366openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fonc.2026.1771804openalex-snapshot
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inferred← citeshttps://doi.org/10.3389/fpubh.2025.1635381openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/bioengineering13010111openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/diagnostics15091170openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/electronics13193806openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/electronics15071519openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/electronics15184126openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/info17020212openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/jcto2020005openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/make8030076openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/sym17111808openalex-snapshot
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inferred← citeshttps://doi.org/10.37349/edht.2026.1011102openalex-snapshot
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inferred← citeshttps://doi.org/10.4018/979-8-3373-8904-2.ch015openalex-snapshot
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inferred← citeshttps://doi.org/10.4018/979-8-3693-9501-1.ch004openalex-snapshot
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inferred← citeshttps://doi.org/10.4236/ijis.2025.151002openalex-snapshot
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inferred← citeshttps://doi.org/10.54203/scil.2026.wvj70openalex-snapshot
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inferred← citeshttps://doi.org/10.59324/ejmhr.2026.4(1).01openalex-snapshot
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inferred← citeshttps://doi.org/10.65116/vitascientia.v1i1.rev.01openalex-snapshot
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inferred← citeshttps://doi.org/10.7717/peerj-cs.3989openalex-snapshot
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