Published on 13.04.18 in Vol 6, No 2 (2018): Apr-Jun
Works citing "Privacy-Preserving Patient Similarity Learning in a Federated Environment: Development and Analysis"
According to Crossref, the following articles are citing this article (DOI 10.2196/medinform.7744):
(note that this is only a small subset of citations)
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Goecks J, Jalili V, Heiser LM, Gray JW. How Machine Learning Will Transform Biomedicine. Cell 2020;181(1):92
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Wang Y, Wen A, Liu S, Hersh W, Bedrick S, Liu H. Test collections for electronic health record-based clinical information retrieval. JAMIA Open 2019;2(3):360
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Kapa S, Halamka J, Raskar R. Contact Tracing to Manage COVID-19 Spread—Balancing Personal Privacy and Public Health. Mayo Clinic Proceedings 2020;95(7):1320
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Kim M, Lee J, Ohno-Machado L, Jiang X. Secure and Differentially Private Logistic Regression for Horizontally Distributed Data. IEEE Transactions on Information Forensics and Security 2020;15:695
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Jia Z, Zeng X, Duan H, Lu X, Li H. A patient-similarity-based model for diagnostic prediction. International Journal of Medical Informatics 2020;135:104073
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Liu Y, Tian M, Xu C, Zhao L. Neural network feature learning based on image self-encoding. International Journal of Advanced Robotic Systems 2020;17(2):172988142092165
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Rieke N, Hancox J, Li W, Milletarì F, Roth HR, Albarqouni S, Bakas S, Galtier MN, Landman BA, Maier-Hein K, Ourselin S, Sheller M, Summers RM, Trask A, Xu D, Baust M, Cardoso MJ. The future of digital health with federated learning. npj Digital Medicine 2020;3(1)
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Yin F, Lin Z, Kong Q, Xu Y, Li D, Theodoridis S, Cui SR. FedLoc: Federated Learning Framework for Data-Driven Cooperative Localization and Location Data Processing. IEEE Open Journal of Signal Processing 2020;1:187
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Park C, Seo SW, Kang N, Ko B, Choi BW, Park C, Chang DK, Kim H, Kim H, Lee H, Jang J, Ye JC, Jeon JH, Seo JB, Kim KJ, Jung K, Kim N, Paek S, Shin S, Yoo S, Choi YS, Kim Y, Yoon H. Artificial Intelligence in Health Care: Current Applications and Issues. Journal of Korean Medical Science 2020;35(42)
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Si Y, Du J, Li Z, Jiang X, Miller T, Wang F, Jim Zheng W, Roberts K. Deep representation learning of patient data from Electronic Health Records (EHR): A systematic review. Journal of Biomedical Informatics 2021;115:103671
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Xu J, Glicksberg BS, Su C, Walker P, Bian J, Wang F. Federated Learning for Healthcare Informatics. Journal of Healthcare Informatics Research 2021;5(1):1
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Liu JC, Goetz J, Sen S, Tewari A. Learning From Others Without Sacrificing Privacy: Simulation Comparing Centralized and Federated Machine Learning on Mobile Health Data. JMIR mHealth and uHealth 2021;9(3):e23728
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Kirienko M, Sollini M, Ninatti G, Loiacono D, Giacomello E, Gozzi N, Amigoni F, Mainardi L, Lanzi PL, Chiti A. Distributed learning: a reliable privacy-preserving strategy to change multicenter collaborations using AI. European Journal of Nuclear Medicine and Molecular Imaging 2021;48(12):3791
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Feki I, Ammar S, Kessentini Y, Muhammad K. Federated learning for COVID-19 screening from Chest X-ray images. Applied Soft Computing 2021;106:107330
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Lee T, Lee J, Jun C. Bilingual autoencoder-based efficient harmonization of multi-source private data for accurate predictive modeling. Information Sciences 2021;568:403
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Abdulkareem M, Petersen SE. The Promise of AI in Detection, Diagnosis, and Epidemiology for Combating COVID-19: Beyond the Hype. Frontiers in Artificial Intelligence 2021;4
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Danilevicz MF, Bayer PE, Nestor BJ, Bennamoun M, Edwards D. Resources for image-based high-throughput phenotyping in crops and data sharing challenges. Plant Physiology 2021;187(2):699
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Rahman A, Hossain MS, Muhammad G, Kundu D, Debnath T, Rahman M, Khan MSI, Tiwari P, Band SS. Federated learning-based AI approaches in smart healthcare: concepts, taxonomies, challenges and open issues. Cluster Computing 2023;26(4):2271
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Zhang A, Xing L, Zou J, Wu JC. Shifting machine learning for healthcare from development to deployment and from models to data. Nature Biomedical Engineering 2022;6(12):1330
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Li L, Fan Y, Tse M, Lin K. A review of applications in federated learning. Computers & Industrial Engineering 2020;149:106854
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Bharati S, Mondal MRH, Podder P, Prasath VS. Federated learning: Applications, challenges and future directions. International Journal of Hybrid Intelligent Systems 2022;18(1-2):19
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Li Z, Mao F, Wu C. Can we share models if sharing data is not an option?. Patterns 2022;3(11):100603
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Ogier du Terrail J, Leopold A, Joly C, Béguier C, Andreux M, Maussion C, Schmauch B, Tramel EW, Bendjebbar E, Zaslavskiy M, Wainrib G, Milder M, Gervasoni J, Guerin J, Durand T, Livartowski A, Moutet K, Gautier C, Djafar I, Moisson A, Marini C, Galtier M, Balazard F, Dubois R, Moreira J, Simon A, Drubay D, Lacroix-Triki M, Franchet C, Bataillon G, Heudel P. Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer. Nature Medicine 2023;29(1):135
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Allam A, Feuerriegel S, Rebhan M, Krauthammer M. Analyzing Patient Trajectories With Artificial Intelligence. Journal of Medical Internet Research 2021;23(12):e29812
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Torkzadehmahani R, Nasirigerdeh R, Blumenthal DB, Kacprowski T, List M, Matschinske J, Spaeth J, Wenke NK, Baumbach J. Privacy-Preserving Artificial Intelligence Techniques in Biomedicine. Methods of Information in Medicine 2022;61(S 01):e12
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Che S, Kong Z, Peng H, Sun L, Leow A, Chen Y, He L. Federated Multi-view Learning for Private Medical Data Integration and Analysis. ACM Transactions on Intelligent Systems and Technology 2022;13(4):1
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Silva PR, Vinagre J, Gama J. Towards federated learning: An overview of methods and applications. WIREs Data Mining and Knowledge Discovery 2023;13(2)
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Ogundokun RO, Misra S, Maskeliunas R, Damasevicius R. A Review on Federated Learning and Machine Learning Approaches: Categorization, Application Areas, and Blockchain Technology. Information 2022;13(5):263
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Sun L, Wu J. A Scalable and Transferable Federated Learning System for Classifying Healthcare Sensor Data. IEEE Journal of Biomedical and Health Informatics 2023;27(2):866
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Rahman KMJ, Ahmed F, Akhter N, Hasan M, Amin R, Aziz KE, Islam AKMM, Mukta MSH, Islam AKMN. Challenges, Applications and Design Aspects of Federated Learning: A Survey. IEEE Access 2021;9:124682
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Deng T, Hamdan H, Yaakob R, Kasmiran KA. Personalized Federated Learning for In-Hospital Mortality Prediction of Multi-Center ICU. IEEE Access 2023;11:11652
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Dasaradharami Reddy K, Gadekallu TR, Doulamis AD. A Comprehensive Survey on Federated Learning Techniques for Healthcare Informatics. Computational Intelligence and Neuroscience 2023;2023:1
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Jordan S, Fontaine C, Hendricks-Sturrup R. Selecting Privacy-Enhancing Technologies for Managing Health Data Use. Frontiers in Public Health 2022;10
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Hallock H, Marshall SE, 't Hoen PAC, Nygård JF, Hoorne B, Fox C, Alagaratnam S. Federated Networks for Distributed Analysis of Health Data. Frontiers in Public Health 2021;9
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Danilevicz MF, Gill M, Anderson R, Batley J, Bennamoun M, Bayer PE, Edwards D. Plant Genotype to Phenotype Prediction Using Machine Learning. Frontiers in Genetics 2022;13
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Wang H, Shen H, Li F, Wu Y, Li M, Shi Z, Deng F. Novel PV Power Hybrid Prediction Model Based on FL Co-Training Method. Electronics 2023;12(3):730
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Li Q, Wei X, Lin H, Liu Y, Chen T, Ma X. Inspecting the Running Process of Horizontal Federated Learning via Visual Analytics. IEEE Transactions on Visualization and Computer Graphics 2022;28(12):4085
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Dang TK, Lan X, Weng J, Feng M. Federated Learning for Electronic Health Records. ACM Transactions on Intelligent Systems and Technology 2022;13(5):1
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Yu B, Mao W, Lv Y, Zhang C, Xie Y. A survey on federated learning in data mining. WIREs Data Mining and Knowledge Discovery 2022;12(1)
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Antunes RS, André da Costa C, Küderle A, Yari IA, Eskofier B. Federated Learning for Healthcare: Systematic Review and Architecture Proposal. ACM Transactions on Intelligent Systems and Technology 2022;13(4):1
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Gkoulalas-Divanis A, Vatsalan D, Karapiperis D, Kantarcioglu M. Modern Privacy-Preserving Record Linkage Techniques: An Overview. IEEE Transactions on Information Forensics and Security 2021;16:4966
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Lopez Pineda A, Pourshafeie A, Ioannidis A, Leibold CM, Chan AL, Bustamante CD, Frankovich J, Wojcik GL. Discovering prescription patterns in pediatric acute-onset neuropsychiatric syndrome patients. Journal of Biomedical Informatics 2021;113:103664
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Lee M, Kim S, Kim H, Lee J. Technology Opportunity Discovery using Deep Learning-based Text Mining and a Knowledge Graph. Technological Forecasting and Social Change 2022;180:121718
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Darzidehkalani E, Ghasemi-rad M, van Ooijen P. Federated Learning in Medical Imaging: Part I: Toward Multicentral Health Care Ecosystems. Journal of the American College of Radiology 2022;19(8):969
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Huang W, Barnard AS. Federated data processing and learning for collaboration in the physical sciences. Machine Learning: Science and Technology 2022;3(4):045023
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Navaz AN, T. El-Kassabi H, Serhani MA, Oulhaj A, Khalil K. A Novel Patient Similarity Network (PSN) Framework Based on Multi-Model Deep Learning for Precision Medicine. Journal of Personalized Medicine 2022;12(5):768
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Sadilek A, Liu L, Nguyen D, Kamruzzaman M, Serghiou S, Rader B, Ingerman A, Mellem S, Kairouz P, Nsoesie EO, MacFarlane J, Vullikanti A, Marathe M, Eastham P, Brownstein JS, Arcas BAY, Howell MD, Hernandez J. Privacy-first health research with federated learning. npj Digital Medicine 2021;4(1)
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Topaloglu MY, Morrell EM, Rajendran S, Topaloglu U. In the Pursuit of Privacy: The Promises and Predicaments of Federated Learning in Healthcare. Frontiers in Artificial Intelligence 2021;4
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Chen R, Zhang Y, Dou Z, Chen F, Xie K, Wang S. Data Sharing and Privacy in Pharmaceutical Studies. Current Pharmaceutical Design 2021;27(7):911
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Palihawadana C, Wiratunga N, Wijekoon A, Kalutarage H. FedSim: Similarity guided model aggregation for Federated Learning. Neurocomputing 2022;483:432
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Stripelis D, Thompson PM, Ambite JL. Semi-Synchronous Federated Learning for Energy-Efficient Training and Accelerated Convergence in Cross-Silo Settings. ACM Transactions on Intelligent Systems and Technology 2022;13(5):1
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Aouedi O, Sacco A, Piamrat K, Marchetto G. Handling Privacy-Sensitive Medical Data With Federated Learning: Challenges and Future Directions. IEEE Journal of Biomedical and Health Informatics 2023;27(2):790
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Xu X, Peng H, Bhuiyan MZA, Hao Z, Liu L, Sun L, He L. Privacy-Preserving Federated Depression Detection From Multisource Mobile Health Data. IEEE Transactions on Industrial Informatics 2022;18(7):4788
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Naz S, Phan KT, Chen YP. A comprehensive review of federated learning for COVID‐19 detection. International Journal of Intelligent Systems 2022;37(3):2371
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Khalid N, Qayyum A, Bilal M, Al-Fuqaha A, Qadir J. Privacy-preserving artificial intelligence in healthcare: Techniques and applications. Computers in Biology and Medicine 2023;158:106848
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Gong Y, Li X, Wang L. FedMBC: Personalized federated learning via mutually beneficial collaboration. Computer Communications 2023;205:108
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Li M, Lin Y, Chen H, Aparasu RR. An unsupervised embedding harmonization system for privacy-preserving data mining in healthcare. IISE Transactions on Healthcare Systems Engineering 2024;14(1):1
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Wang Q, He M, Guo L, Chai H. AFEI: adaptive optimized vertical federated learning for heterogeneous multi-omics data integration. Briefings in Bioinformatics 2023;24(5)
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Xu X, Qi Z, Han X, Xu A, Geng Z, He X, Ren Y, Duo Z. Predicting anticancer drug sensitivity on distributed data sources using federated deep learning. Heliyon 2023;9(8):e18615
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Asaadi S, Martins KN, Lee MM, Pantoja JL. Artificial intelligence for the vascular surgeon. Seminars in Vascular Surgery 2023;36(3):394
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Lee T, Kim S, Lee J, Jun C. Word2Vec-based efficient privacy-preserving shared representation learning for federated recommendation system in a cross-device setting. Information Sciences 2023;651:119728
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Petti M, Farina L. Network medicine for patients' stratification: From single‐layer to multi‐omics. WIREs Mechanisms of Disease 2023;15(6)
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Rogers MP, Janjua HM, Walczak S, Baker M, Read M, Cios K, Velanovich V, Pietrobon R, Kuo PC. Artificial Intelligence in Surgical Research: Accomplishments and Future Directions. The American Journal of Surgery 2024;230:82
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Zhang L, Xu J, Vijayakumar P, Sharma PK, Ghosh U. Homomorphic Encryption-Based Privacy-Preserving Federated Learning in IoT-Enabled Healthcare System. IEEE Transactions on Network Science and Engineering 2023;10(5):2864
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Śmietanka M, Pithadia H, Treleaven P. Federated learning for privacy-preserving data access. International Journal of Data Science and Big Data Analytics 2021;1(2):1
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Xu B, Zhang Y, Fan Z, Han L, Shen Z. Patient privacy protection: Generating available medical treatment plans based on federated learning and CBR. Information & Management 2023;:103908
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PHONG LT, PHUONG TT, WANG L, OZAWA S. Frameworks for Privacy-Preserving Federated Learning. IEICE Transactions on Information and Systems 2024;E107.D(1):2
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Malik H, Anees T. Federated learning with deep convolutional neural networks for the detection of multiple chest diseases using chest x-rays. Multimedia Tools and Applications 2024;
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Jiang S, Li Y, Firouzi F, Chakrabarty K. Federated clustered multi-domain learning for health monitoring. Scientific Reports 2024;14(1)
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Song J, Song Z, Zhang J, Gong Y. Privacy-Preserving Identification of Cancer Subtype-Specific Driver Genes Based on Multigenomics Data with Privatedriver. Journal of Computational Biology 2024;31(2):99
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Lee T, Kim S, Lee J, Jun C. HarmoSATE: Harmonized embedding-based self-attentive encoder to improve accuracy of privacy-preserving federated predictive analysis. Information Sciences 2024;662:120265
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Darzi E, Sijtsema NM, van Ooijen PMA. A comparative study of federated learning methods for COVID-19 detection. Scientific Reports 2024;14(1)
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Malhotra R, Bansal A, Kessentini M. Deployment and performance monitoring of docker based federated learning framework for software defect prediction. Cluster Computing 2024;
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Wang R, Qiu H, Gao H, Li C, Dong ZY, Liu J. Adaptive Horizontal Federated Learning-Based Demand Response Baseline Load Estimation. IEEE Transactions on Smart Grid 2024;15(2):1659
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Fu S, Jia H, Vassilaki M, Keloth VK, Dang Y, Zhou Y, Garg M, Petersen RC, St Sauver J, Moon S, Wang L, Wen A, Li F, Xu H, Tao C, Fan J, Liu H, Sohn S. FedFSA: Hybrid and federated framework for functional status ascertainment across institutions. Journal of Biomedical Informatics 2024;152:104623
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Zidi I, Issaoui I, El Khediri S, Khan RU. An approach based on NSGA-III algorithm for solving the multi-objective federated learning optimization problem. International Journal of Information Technology 2024;
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According to Crossref, the following books are citing this article (DOI 10.2196/medinform.7744):
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Silva S, Altmann A, Gutman B, Lorenzi M. Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning. 2020. Chapter 20:201
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Sharma S, Kesarwani A, Maheshwari S, Rai BK. Federated Learning for IoT Applications. 2022. Chapter 16:243
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Farjana A, Makkar A. Recent Trends in Image Processing and Pattern Recognition. 2023. Chapter 9:120
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Schneider P, Xhafa F. Anomaly Detection and Complex Event Processing over IoT Data Streams. 2022. :149
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Patra G, Bhimala KR, Marndi A, Chowdhury S, Rahaman J, Nandi S, Sarkar RR, Gouda K, Ramesh K, Barnwal RP, Raj S, Saini A. Deep Learning. 2023. :107
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. Federated Learning. 2022. Chapter 23:499
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Ramesh V, S. H, Sundaram SG, N. B. P, G. R. H. Handbook of Research on Design, Deployment, Automation, and Testing Strategies for 6G Mobile Core Network. 2022. chapter 19:382
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Long G, Shen T, Tan Y, Gerrard L, Clarke A, Jiang J. Humanity Driven AI. 2022. Chapter 6:113
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Wang D, Wang T. Soft Computing in Data Science. 2023. Chapter 6:76
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Sahoo P, Saha S, Mondal S, Chowdhury S, Gowda S. Neural Information Processing. 2023. Chapter 7:77
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Ameijeiras-Rodriguez C, Rb-Silva R, Diniz JM, Souza J, Freitas A. Computational Science – ICCS 2023. 2023. Chapter 25:313
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Gupta M, Sharma P, Kalra R. Federated Learning and AI for Healthcare 5.0. 2023. chapter 6:104
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