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Applications of Federated Learning in Mobile Health: Scoping Review
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Bayesian Inference Federated Learning for Heart Rate Prediction
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Artificial Intelligence XXXVIII
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Context-Aware Support for Cardiac Health Monitoring Using Federated Machine Learning
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mHealthDroid: A Novel Framework for Agile Development of Mobile Health Applications
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Human Daily Activity and Fall Recognition Using a Smartphone’s Acceleration Sensor
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The Hamilton Rating Scale for Depression
inferredcites →https://doi.org/10.1007/978-981-16-0575-8_5openalex-snapshot
Resource-Constrained Federated Learning with Heterogeneous Labels and Models for Human Activity Recognition
inferredcites →https://doi.org/10.1016/j.knosys.2021.107338openalex-snapshot
A federated learning system with enhanced feature extraction for human activity recognition
inferredcites →https://doi.org/10.1016/j.knosys.2021.107763openalex-snapshot
Designing ECG monitoring healthcare system with federated transfer learning and explainable AI
inferredcites →https://doi.org/10.1016/j.pmcj.2017.01.008openalex-snapshot
Position-aware activity recognition with wearable devices
inferredcites →https://doi.org/10.1016/j.procs.2014.07.009openalex-snapshot
A Study on Human Activity Recognition Using Accelerometer Data from Smartphones
inferredcites →https://doi.org/10.1038/s41746-020-00323-1openalex-snapshot
The future of digital health with federated learning
inferredcites →https://doi.org/10.1109/51.932724openalex-snapshot
The impact of the MIT-BIH Arrhythmia Database
inferredcites →https://doi.org/10.1109/access.2019.2940729openalex-snapshot
Smartphone and Smartwatch-Based Biometrics Using Activities of Daily Living
inferredcites →https://doi.org/10.1109/bibm52615.2021.9669330openalex-snapshot
FedIO: Bridge Inner- and Outer-hospital Information for Perioperative Complications Prognostic Prediction via Federated Learning
inferredcites →https://doi.org/10.1109/bigdata50022.2020.9377795openalex-snapshot
Heterogeneous Similarity Graph Neural Network on Electronic Health Records
inferredcites →https://doi.org/10.1109/csci.2016.0043openalex-snapshot
A Collaborative Privacy-Preserving Deep Learning System in Distributed Mobile Environment
inferredcites →https://doi.org/10.1109/cvpr.2017.587openalex-snapshot
iCaRL: Incremental Classifier and Representation Learning
inferredcites →https://doi.org/10.1109/date.2009.5090858openalex-snapshot
Multi-core for mobile phones
inferredcites →https://doi.org/10.1109/glocom.2015.7417841openalex-snapshot
Privacy-Preserving Collaborative Learning for Mobile Health Monitoring
inferredcites →https://doi.org/10.1109/iccad51958.2021.9643454openalex-snapshot
Federated Contrastive Learning for Dermatological Disease Diagnosis via On-device Learning (Invited Paper)
inferredcites →https://doi.org/10.1109/infocom42981.2021.9488776openalex-snapshot
FedSens: A Federated Learning Approach for Smart Health Sensing with Class Imbalance in Resource Constrained Edge Computing
inferredcites →https://doi.org/10.1109/inss.2010.5573462openalex-snapshot
Collecting complex activity datasets in highly rich networked sensor environments
inferredcites →https://doi.org/10.1109/iswc.2012.13openalex-snapshot
Introducing a New Benchmarked Dataset for Activity Monitoring
inferredcites →https://doi.org/10.1109/iwcmc51323.2021.9498820openalex-snapshot
Deep Federated Learning for IoT-based Decentralized Healthcare Systems
inferredcites →https://doi.org/10.1109/jiot.2020.2991416openalex-snapshot
Personalized Federated Learning With Differential Privacy
inferredcites →https://doi.org/10.1109/mis.2020.2988604openalex-snapshot
FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare
inferredcites →https://doi.org/10.1109/msp.2020.2975749openalex-snapshot
Federated Learning: Challenges, Methods, and Future Directions
inferredcites →https://doi.org/10.1109/tcbb.2016.2515610openalex-snapshot
Private Data Analytics on Biomedical Sensing Data via Distributed Computation
inferredcites →https://doi.org/10.1109/tii.2021.3113708openalex-snapshot
Privacy-Preserving Federated Depression Detection From Multisource Mobile Health Data
inferredcites →https://doi.org/10.1109/titb.2009.2036165openalex-snapshot
Wearable Assistant for Parkinson’s Disease Patients With the Freezing of Gait Symptom
inferredcites →https://doi.org/10.1109/tmc.2020.3045266openalex-snapshot
FedHome: Cloud-Edge Based Personalized Federated Learning for In-Home Health Monitoring
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FedHAR: Semi-Supervised Online Learning for Personalized Federated Human Activity Recognition
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The SWELL Knowledge Work Dataset for Stress and User Modeling Research
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Privacy-Preserving Collaborative Deep Learning with Application to Human Activity Recognition
inferredcites →https://doi.org/10.1145/3133956.3133982openalex-snapshot
Practical Secure Aggregation for Privacy-Preserving Machine Learning
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A Survey on Homomorphic Encryption Schemes
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Introducing WESAD, a Multimodal Dataset for Wearable Stress and Affect Detection
inferredcites →https://doi.org/10.1145/3378679.3394529openalex-snapshot
Privacy-preserving activity and health monitoring on databox
inferredcites →https://doi.org/10.1145/3404397.3404410openalex-snapshot
FEEL: A Federated Edge Learning System for Efficient and Privacy-Preserving Mobile Healthcare
inferredcites →https://doi.org/10.1145/3410530.3414321openalex-snapshot
Evaluation of federated learning aggregation algorithms
inferredcites →https://doi.org/10.1145/3428152openalex-snapshot
Privacy-preserving Federated Deep Learning for Wearable IoT-based Biomedical Monitoring
inferredcites →https://doi.org/10.1145/3442381.3450006openalex-snapshot
Meta-HAR: Federated Representation Learning for Human Activity Recognition
inferredcites →https://doi.org/10.1145/3477084.3484950openalex-snapshot
Integrating federated learning with IoMT for managing obesity in smart city
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Robust EEG Channel Selection across Subjects for Brain-Computer Interfaces
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A Rating Scale for Mania: Reliability, Validity and Sensitivity
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The Digitization of Healthcare: Boundary Risks, Emotion, and Consumer Willingness to Disclose Personal Health Information
inferredcites →https://doi.org/10.1561/9781601984616openalex-snapshot
Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
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Electronic Patient-Reported Outcome Measures in Radiation Oncology: Initial Experience After Workflow Implementation
inferredcites →https://doi.org/10.2196/23728openalex-snapshot
Learning From Others Without Sacrificing Privacy: Simulation Comparing Centralized and Federated Machine Learning on Mobile Health Data
inferredcites →https://doi.org/10.25300/misq/2021/15574openalex-snapshot
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Pima Indians Diabetes Database Processing through EBBM-Optimized UTM Model
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Artificial intelligence and algorithmic bias: implications for health systems
inferredcites →https://doi.org/10.7326/m18-0850openalex-snapshot
PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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inferred← citeshttps://doi.org/10.1007/978-3-031-96265-3_12openalex-snapshot
Federated Learning: A Paradigm Shift in Healthcare Data Privacy
inferred← citeshttps://doi.org/10.1007/978-3-031-96724-5_8openalex-snapshot
Discussions and Conclusions
inferred← citeshttps://doi.org/10.1007/978-3-032-16711-8_10openalex-snapshot
AI Without Borders: Federated Learning for Intelligent Edge Computing
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Advancements and Challenges in Federated Learning for Privacy-Preserving Smart Healthcare: A Review
inferred← citeshttps://doi.org/10.1007/s00607-024-01364-0openalex-snapshot
Simulafed: an enhanced federated simulated environment for privacy and security in health
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inferred← citeshttps://doi.org/10.1007/s10586-025-05106-5openalex-snapshot
Optimizing Client Selection in Federated Learning Base on Genetic Algorithm
inferred← citeshttps://doi.org/10.1007/s10791-025-09686-zopenalex-snapshot
Cyber threats in mobile healthcare applications: systematic review of enabling technologies, threat models, detection approaches, and future directions
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Analyzing the Impact of Personalization on Fairness in Federated Learning for Healthcare
inferred← citeshttps://doi.org/10.1016/j.aei.2024.102411openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.compbiomed.2024.108344openalex-snapshot
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How are Machine Learning and Artificial Intelligence Used in Digital Behavior Change Interventions? A Scoping Review
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FedLDR: Federated optimization with label distribution-aware representations
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inferred← citeshttps://doi.org/10.1109/3scea68071.2026.11602815openalex-snapshot
Into the Wild: Bringing Federated Learning to Life
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An Insight into Federated Learning: A Collaborative Approach for Machine Learning
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Study of MobileNets Model in Federated Learning
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Enhancing Edge-based Cardiovascular Diagnosis through Federated Learning and IoT
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