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The FeatureCloud Platform for Federated Learning in Biomedicine: Unified Approach
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Calibrating Noise to Sensitivity in Private Data Analysis
inferredcites →https://doi.org/10.1007/978-3-030-60548-3_20openalex-snapshot
Fed-BioMed: A General Open-Source Frontend Framework for Federated Learning in Healthcare
inferredcites →https://doi.org/10.1007/978-3-319-66808-6_24openalex-snapshot
The More the Merrier - Federated Learning from Local Sphere Recommendations
inferredcites →https://doi.org/10.1016/0095-0696(78)90006-2openalex-snapshot
Hedonic housing prices and the demand for clean air
inferredcites →https://doi.org/10.1016/j.cell.2018.02.052openalex-snapshot
An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics
inferredcites →https://doi.org/10.1016/j.tips.2019.06.004openalex-snapshot
Advancing Drug Discovery via Artificial Intelligence
inferredcites →https://doi.org/10.1016/j.tips.2019.07.013openalex-snapshot
Advancing Drug Discovery via Artificial Intelligence
inferredcites →https://doi.org/10.1021/acs.molpharmaceut.5b00982openalex-snapshot
Applications of Deep Learning in Biomedicine
inferredcites →https://doi.org/10.1038/nature22985openalex-snapshot
Erratum: Corrigendum: Dermatologist-level classification of skin cancer with deep neural networks
inferredcites →https://doi.org/10.1038/s41551-018-0305-zopenalex-snapshot
Artificial intelligence in healthcare
inferredcites →https://doi.org/10.1038/s41591-020-1041-yopenalex-snapshot
Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist
inferredcites →https://doi.org/10.1038/s41592-021-01241-0openalex-snapshot
The AIMe registry for artificial intelligence in biomedical research
inferredcites →https://doi.org/10.1038/s41598-020-69250-1openalex-snapshot
Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data
inferredcites →https://doi.org/10.1038/s42256-021-00390-3openalex-snapshot
Adversarial interference and its mitigations in privacy-preserving collaborative machine learning
inferredcites →https://doi.org/10.1093/bioinformatics/btac065openalex-snapshot
Federated Random Forests can improve local performance of predictive models for various healthcare applications
inferredcites →https://doi.org/10.1117/12.148698openalex-snapshot
Nuclear feature extraction for breast tumor diagnosis
inferredcites →https://doi.org/10.1117/12.2520275openalex-snapshot
Model poisoning attacks against distributed machine learning systems
inferredcites →https://doi.org/10.1145/3133956.3133982openalex-snapshot
Practical Secure Aggregation for Privacy-Preserving Machine Learning
inferredcites →https://doi.org/10.1145/3214303openalex-snapshot
A Survey on Homomorphic Encryption Schemes
inferredcites →https://doi.org/10.1145/3286490.3286559openalex-snapshot
A Performance Evaluation of Federated Learning Algorithms
inferredcites →https://doi.org/10.1145/96602.96604openalex-snapshot
Federated database systems for managing distributed, heterogeneous, and autonomous databases
inferredcites →https://doi.org/10.1163/2210-7886_asc-42673aopenalex-snapshot
42673a, 1883-02-23, D?PLER
inferredcites →https://doi.org/10.1186/isrctn12348322openalex-snapshot
Comparing COVID-19 vaccine schedule combinations in adolescents (Com-COV3)
inferredcites →https://doi.org/10.1186/s13059-021-02553-2openalex-snapshot
Flimma: a federated and privacy-aware tool for differential gene expression analysis
inferredcites →https://doi.org/10.1186/s13059-021-02562-1openalex-snapshot
sPLINK: a hybrid federated tool as a robust alternative to meta-analysis in genome-wide association studies
inferredcites →https://doi.org/10.1200/jco.1994.12.3.601openalex-snapshot
Prospective evaluation of prognostic variables from patient-completed questionnaires. North Central Cancer Treatment Group.
inferredcites →https://doi.org/10.1371/journal.pdig.0000101openalex-snapshot
Privacy-aware multi-institutional time-to-event studies
inferredcites →https://doi.org/10.1371/journal.pone.0177459openalex-snapshot
Singularity: Scientific containers for mobility of compute
inferredcites →https://doi.org/10.1561/0400000042openalex-snapshot
The Algorithmic Foundations of Differential Privacy
inferredcites →https://doi.org/10.1561/2200000083openalex-snapshot
Advances and Open Problems in Federated Learning
inferredcites →https://doi.org/10.21105/joss.02166openalex-snapshot
COINSTAC: Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation
inferredcites →https://doi.org/10.2196/20891openalex-snapshot
Federated Learning on Clinical Benchmark Data: Performance Assessment
inferredcites →https://doi.org/10.48550/arxiv.1811.04017openalex-snapshot
A generic framework for privacy preserving deep learning
inferredcites →https://doi.org/10.48550/arxiv.2003.02133openalex-snapshot
Threats to Federated Learning: A Survey
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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AI ‐Powered Personalization Across Digital Ecosystems: A Trust‐Centric Perspective on Intelligent, Ethical, and Adaptive User‐Centric Systems
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Multi‐omics biomarkers for intestinal infection and inflammation in inflammatory bowel disease: Current evidence, translational challenges, and diagnostic opportunities
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Federated Learning in Agents Based Cyber-Physical Systems
inferred← citeshttps://doi.org/10.1007/978-3-031-96380-3_23openalex-snapshot
Privacy-Enhancing Technologies in Federated Learning: A Systematic Review
inferred← citeshttps://doi.org/10.1007/978-981-96-4566-4_23openalex-snapshot
GAN-Based Adaptive Trigger Generation and Target Gradient Alignment in Vertical Federated Learning Backdoor Attacks
inferred← citeshttps://doi.org/10.1007/s10618-023-00983-zopenalex-snapshot
Federated singular value decomposition for high-dimensional data
inferred← citeshttps://doi.org/10.1007/s13748-025-00384-xopenalex-snapshot
Enhanced federated learning framework for handling heterogeneity in medical image data
inferred← citeshttps://doi.org/10.1016/j.array.2026.100725openalex-snapshot
On the power and limits of foundation model image embeddings for privacy-preserving federated learning
inferred← citeshttps://doi.org/10.1016/j.compbiolchem.2025.108852openalex-snapshot
From 16S rRNA to deep learning: Evolution of computational approaches in human microbiome studies
inferred← citeshttps://doi.org/10.1016/j.csbj.2024.08.024openalex-snapshot
Privacy-preserving decentralized learning methods for biomedical applications
inferred← citeshttps://doi.org/10.1016/j.engappai.2026.115017openalex-snapshot
Toward brain magnetic resonance imaging analysis intelligence: A review of federated learning and visual foundation models
inferred← citeshttps://doi.org/10.1016/j.jii.2025.100827openalex-snapshot
On the disagreement problem in Human-in-the-Loop federated machine learning
inferred← citeshttps://doi.org/10.1016/j.mlwa.2026.100890openalex-snapshot
Site-Level fine-tuning with progressive layer freezing: Towards robust prediction of bronchopulmonary dysplasia from day-1 chest radiographs in extremely preterm infants
inferred← citeshttps://doi.org/10.1016/j.xpro.2025.103771openalex-snapshot
Protocol for implementing the nested model for AI design and validation in compliance with AI regulations
inferred← citeshttps://doi.org/10.1038/s41598-024-72748-7openalex-snapshot
Collaborative weighting in federated graph neural networks for disease classification with the human-in-the-loop
inferred← citeshttps://doi.org/10.1038/s41746-025-01809-6openalex-snapshot
Design specifications for biomedical virtual twins in engineered adoptive cellular immunotherapies
inferred← citeshttps://doi.org/10.1038/s43588-025-00832-7openalex-snapshot
Privacy-preserving multicenter differential protein abundance analysis with FedProt
inferred← citeshttps://doi.org/10.1080/1206212x.2025.2496913openalex-snapshot
Healthcare federated learning: a survey of applications and frameworks
inferred← citeshttps://doi.org/10.1080/15265161.2026.2637093openalex-snapshot
Federation Opacity and the Promise of Federated Learning in Healthcare
inferred← citeshttps://doi.org/10.1109/bigdata59044.2023.10386466openalex-snapshot
Differentially Private Federated Learning: Privacy and Utility Analysis of Output Perturbation and DP-SGD
inferred← citeshttps://doi.org/10.1109/bigdata59044.2023.10386579openalex-snapshot
A Comparison of Federated Aggregation Strategies and Architectures for Next-word Prediction
inferred← citeshttps://doi.org/10.1109/flta63145.2024.10840050openalex-snapshot
Flotta: A Secure and Flexible Spark-Inspired Federated Learning Framework
inferred← citeshttps://doi.org/10.1109/trustcom60117.2023.00167openalex-snapshot
Analysing Utility Loss in Federated Learning with Differential Privacy
inferred← citeshttps://doi.org/10.1111/1751-7915.70027openalex-snapshot
AI in microbiome‐related healthcare
inferred← citeshttps://doi.org/10.1145/3843774openalex-snapshot
Starfish-FL: Harnessing Agentic Federated Analytics
inferred← citeshttps://doi.org/10.1177/20552076261466806openalex-snapshot
Lessons from federated networks for implementing the European health data space. Empirical study
inferred← citeshttps://doi.org/10.1177/22143602241296276openalex-snapshot
Privacy-by-Design with Federated Learning will drive future Rare Disease Research
inferred← citeshttps://doi.org/10.1186/s12874-026-02785-5openalex-snapshot
Privacy-preserving federated prediction of health outcomes using multi-center survey data
inferred← citeshttps://doi.org/10.1186/s12903-026-08388-2openalex-snapshot
Automatic detection of multi-site oral squamous cell carcinoma based on privacy-preserving federated learning
inferred← citeshttps://doi.org/10.1186/s13040-026-00582-wopenalex-snapshot
Clifti-GPT: privacy-preserving federated fine-tuning and transferable inference of foundation models on clinical single-cell data
inferred← citeshttps://doi.org/10.1186/s13059-025-03684-6openalex-snapshot
FedscGen: privacy-preserving federated batch effect correction of single-cell RNA sequencing data
inferred← citeshttps://doi.org/10.1515/jib-2022-0032openalex-snapshot
Federated machine learning for a facilitated implementation of Artificial Intelligence in healthcare – a proof of concept study for the prediction of coronary artery calcification scores
inferred← citeshttps://doi.org/10.2196/47652openalex-snapshot
Privacy-Preserving Federated Survival Support Vector Machines for Cross-Institutional Time-To-Event Analysis: Algorithm Development and Validation
inferred← citeshttps://doi.org/10.2196/55496openalex-snapshot
Accessible Ecosystem for Clinical Research (Federated Learning for Everyone): Development and Usability Study
inferred← citeshttps://doi.org/10.3389/fdgth.2025.1644291openalex-snapshot
Technical and legal aspects of federated learning in bioinformatics: applications, challenges and opportunities
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