Truly privacy-preserving federated analytics for precision medicine with multiparty homomorphic encryption

D Froelicher, JR Troncoso-Pastoriza, JL Raisaro… - Nature …, 2021 - nature.com
Using real-world evidence in biomedical research, an indispensable complement to clinical
trials, requires access to large quantities of patient data that are typically held separately by …

[HTML][HTML] Revolutionizing medical data sharing using advanced privacy-enhancing technologies: technical, legal, and ethical synthesis

J Scheibner, JL Raisaro, JR Troncoso-Pastoriza… - Journal of medical …, 2021 - jmir.org
Multisite medical data sharing is critical in modern clinical practice and medical research.
The challenge is to conduct data sharing that preserves individual privacy and data utility …

AI in microbiome‐related healthcare

N Probul, Z Huang, CC Saak… - Microbial …, 2024 - Wiley Online Library
Artificial intelligence (AI) has the potential to transform clinical practice and healthcare.
Following impressive advancements in fields such as computer vision and medical imaging …

[HTML][HTML] The FeatureCloud platform for federated learning in biomedicine: unified approach

J Matschinske, J Späth, M Bakhtiari, N Probul… - Journal of Medical …, 2023 - jmir.org
Background Machine learning and artificial intelligence have shown promising results in
many areas and are driven by the increasing amount of available data. However, these data …

Enhancing data standards to advance translation in spinal cord injury

VK Noonan, S Humphreys, F Biering-Sørensen… - Experimental …, 2025 - Elsevier
Data standards are available for spinal cord injury (SCI). The International SCI Data Sets
were created in 2002 and there are currently 27 freely available. In 2014 the National …

Federated Random Forests can improve local performance of predictive models for various healthcare applications

AC Hauschild, M Lemanczyk, J Matschinske… - …, 2022 - academic.oup.com
Motivation Limited data access has hindered the field of precision medicine from exploring
its full potential, eg concerning machine learning and privacy and data protection rules. Our …

Privacy-preserving artificial intelligence techniques in biomedicine

R Torkzadehmahani, R Nasirigerdeh… - … of information in …, 2022 - thieme-connect.com
Background Artificial intelligence (AI) has been successfully applied in numerous scientific
domains. In biomedicine, AI has already shown tremendous potential, eg, in the …

Federated learning and Indigenous genomic data sovereignty

N Boscarino, RA Cartwright, K Fox… - Nature Machine …, 2022 - nature.com
Indigenous peoples are under-represented in genomic datasets, which can lead to limited
accuracy and utility of machine learning models in precision health. While open data sharing …

[HTML][HTML] Sharing Data With Shared Benefits: Artificial Intelligence Perspective

M Tajabadi, L Grabenhenrich, A Ribeiro… - Journal of Medical …, 2023 - jmir.org
Artificial intelligence (AI) and data sharing go hand in hand. In order to develop powerful AI
models for medical and health applications, data need to be collected and brought together …

TrustGWAS: A full-process workflow for encrypted GWAS using multi-key homomorphic encryption and pseudorandom number perturbation

M Yang, C Zhang, X Wang, X Liu, S Li, J Huang… - Cell Systems, 2022 - cell.com
The statistical power of genome-wide association studies (GWASs) is affected by the
effective sample size. However, the privacy and security concerns associated with individual …