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Machine-Learning-Based IoT–Edge Computing Healthcare Solutions
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1 of the 32 references listed on this page is in the Retraction Watch database as retracted (export 2026-11-11): 10.1007/s00500-021-06514-6 (notice 2024-07-14).
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/ett.3710openalex-snapshot
Edge computing in smart health care systems: Review, challenges, and research directions
inferredcites →https://doi.org/10.1007/s00500-021-06514-6openalex-snapshot
RETRACTED ARTICLE: Cognitive computing-based COVID-19 detection on Internet of things-enabled edge computing environment
inferredcites →https://doi.org/10.1016/b978-0-12-817774-7.00009-0openalex-snapshot
Communications and internet of things for microgrids, smart buildings, and homes
inferredcites →https://doi.org/10.1016/j.future.2020.07.047openalex-snapshot
An intelligent healthcare monitoring framework using wearable sensors and social networking data
inferredcites →https://doi.org/10.1057/s41264-022-00161-0openalex-snapshot
The transformative potential of banking service domains with the emergence of FinTechs
inferredcites →https://doi.org/10.1109/access.2019.2945338openalex-snapshot
Understanding Edge Computing: Engineering Evolution With Artificial Intelligence
inferredcites →https://doi.org/10.1109/access.2021.3092304openalex-snapshot
Energy Management in Smart Buildings and Homes: Current Approaches, a Hypothetical Solution, and Open Issues and Challenges
inferredcites →https://doi.org/10.1109/access.2022.3143793openalex-snapshot
FETCH: A Deep Learning-Based Fog Computing and IoT Integrated Environment for Healthcare Monitoring and Diagnosis
inferredcites →https://doi.org/10.1109/bigdata50022.2020.9377873openalex-snapshot
A Framework for Edge-Assisted Healthcare Data Analytics using Federated Learning
inferredcites →https://doi.org/10.1109/globecom42002.2020.9348167openalex-snapshot
A Hierarchical Hybrid Intrusion Detection Approach in IoT Scenarios
inferredcites →https://doi.org/10.1109/iemcon53756.2021.9623076openalex-snapshot
Resource Allocation in Multi-access Edge Computing: Optimization and Machine Learning
inferredcites →https://doi.org/10.1109/iscon52037.2021.9702478openalex-snapshot
IoT based Smart Agriculture System
inferredcites →https://doi.org/10.1109/jiot.2017.2749401openalex-snapshot
Internet of Things for Smart Railway: Feasibility and Applications
inferredcites →https://doi.org/10.1109/mwc.001.2000345openalex-snapshot
Edge Intelligence for Empowering IoT-Based Healthcare Systems
inferredcites →https://doi.org/10.1109/mwc.2019.1800411openalex-snapshot
Artificial Intelligence Empowered Edge Computing and Caching for Internet of Vehicles
inferredcites →https://doi.org/10.1109/tetc.2020.3033532openalex-snapshot
Blockchain-Based Trust Management for Internet of Vehicles
inferredcites →https://doi.org/10.1109/tii.2019.2902878openalex-snapshot
Artificial Intelligence-Driven Mechanism for Edge Computing-Based Industrial Applications
inferredcites →https://doi.org/10.1109/tii.2019.2903342openalex-snapshot
Towards Secure Industrial IoT: Blockchain System With Credit-Based Consensus Mechanism
inferredcites →https://doi.org/10.1109/tii.2019.2963728openalex-snapshot
Blockchain-Based Mobile Crowd Sensing in Industrial Systems
inferredcites →https://doi.org/10.1109/tsc.2019.2949801openalex-snapshot
Groupchain: Towards a Scalable Public Blockchain in Fog Computing of IoT Services Computing
inferredcites →https://doi.org/10.1109/wts51064.2021.9433711openalex-snapshot
A Novel Blockchain-Based Trust Management Scheme for Vehicular Networks
inferredcites →https://doi.org/10.14569/ijacsa.2016.070947openalex-snapshot
Internet of Things based Expert System for Smart Agriculture
inferredcites →https://doi.org/10.23919/icn.2021.0005openalex-snapshot
Internet of things for high-speed railways
inferredcites →https://doi.org/10.3233/ais-170440openalex-snapshot
Internet of things for smart agriculture: Technologies, practices and future direction
inferredcites →https://doi.org/10.32604/cmc.2022.015707openalex-snapshot
Efficient Resource Allocation in Fog Computing Using QTCS Model
inferredcites →https://doi.org/10.3390/app12073396openalex-snapshot
IoT-Enabled Smart Agriculture: Architecture, Applications, and Challenges
inferredcites →https://doi.org/10.3390/app12115646openalex-snapshot
Privacy-Preserving Data Mining on Blockchain-Based WSNs
inferredcites →https://doi.org/10.3390/app12125893openalex-snapshot
Optimal Machine Learning Based Privacy Preserving Blockchain Assisted Internet of Things with Smart Cities Environment
inferredcites →https://doi.org/10.3390/electronics11030494openalex-snapshot
Threat Analysis and Distributed Denial of Service (DDoS) Attack Recognition in the Internet of Things (IoT)
inferredcites →https://doi.org/10.3390/s21217016openalex-snapshot
A Deep Learning-Based Intrusion Detection System for MQTT Enabled IoT
inferredcites →https://doi.org/10.3390/su14095200openalex-snapshot
Trusted Blockchain-Driven IoT Security Consensus Mechanism
inferredcites →https://doi.org/10.36548/jucct.2021.1.004openalex-snapshot
Optimized Mobile Edge Computing Framework for IoT based Medical Sensor Network Nodes
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Edge Computing in Healthcare Using Machine Learning: A Systematic Literature Review
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Strategic Approaches to Efficient Data Aggregation and Malicious Node Detection in IoT-Enabled Healthcare Systems
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inferred← citeshttps://doi.org/10.1007/s42600-025-00437-zopenalex-snapshot
Edge-based real-time diagnosis of pediatric pneumonia using lightweight CNNs and chest X-rays
inferred← citeshttps://doi.org/10.1007/s44196-025-01100-2openalex-snapshot
EMLSCF-FCH: A Secure and Efficient Machine Learning-Based Framework for Fog Computing in Healthcare
inferred← citeshttps://doi.org/10.1016/j.abst.2025.08.006openalex-snapshot
Machine learning and IoT in healthcare: Recent advancements, challenges & future direction
inferred← citeshttps://doi.org/10.1016/j.asej.2025.103553openalex-snapshot
Efficient data handling in smart healthcare using Quotient Hash Trees and gaussian hilbert regression
inferred← citeshttps://doi.org/10.1016/j.compag.2025.111188openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.eij.2025.100788openalex-snapshot
Enhancing personalization in IoT-based health monitoring via generative AI and transfer learning
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inferred← citeshttps://doi.org/10.1016/j.iot.2025.101553openalex-snapshot
Reducing communication overhead in the IoT–edge–cloud continuum: A survey on protocols and data reduction strategies
inferred← citeshttps://doi.org/10.1016/j.jksuci.2024.101940openalex-snapshot
Classification of Alzheimer’s disease using MRI data based on Deep Learning Techniques
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Hybrid Bayesian and deep learning-based degradation modeling for medical imaging equipment under multi-condition Internet of Medical Things data streams
inferred← citeshttps://doi.org/10.1016/j.rineng.2025.106101openalex-snapshot
AI-based online VoI-aware healthcare and medical monitoring task computing
inferred← citeshttps://doi.org/10.1038/s41598-025-89726-2openalex-snapshot
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inferred← citeshttps://doi.org/10.1038/s41598-025-97065-5openalex-snapshot
Improved security for IoT-based remote healthcare systems using deep learning with jellyfish search optimization algorithm
inferred← citeshttps://doi.org/10.1080/1448837x.2025.2583458openalex-snapshot
SecureFogDL: a federated Transformer framework for secure and intelligent fog computing in healthcare IoT
inferred← citeshttps://doi.org/10.1080/20421338.2026.2638925openalex-snapshot
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Deep Learning Applications in ECG Analysis and Disease Detection: An Investigation Study of Recent Advances
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Real-Time Edge Computing Services for Internet of Things-based Cloud Networks
inferred← citeshttps://doi.org/10.1109/bdkcse67969.2025.11300519openalex-snapshot
Big Data Infrastructure and Analytics Framework for Next-Generation Smart Healthcare Systems
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Performance Modeling and Analysis of Internet of Things Enabled Healthcare Monitoring Systems
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Federated Learning in IoT Environments: Examining the Three-Way See-Saw for Privacy, Model-Performance, and Network-Efficiency
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IoT-Based Heart Disease Monitoring Using Neural Networks for Detecting Arrhythmia and Assessing Hypertrophic Cardiomyopathy(HCM) Risk
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Applications of Fog Computing in Healthcare
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