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Achieving GWAS with homomorphic encryption
BackgroundOne way of investigating how genes affect human traits would be with a genome-wide association study (GWAS). Genetic markers, known as...
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Privacy-preserving approximate GWAS computation based on homomorphic encryption
BackgroundOne of three tasks in a secure genome analysis competition called iDASH 2018 was to develop a solution for privacy-preserving GWAS...
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Optimized homomorphic encryption solution for secure genome-wide association studies
BackgroundGenome-Wide Association Studies (GWAS) refer to observational studies of a genome-wide set of genetic variants across many individuals to...
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Privacy-preserving semi-parallel logistic regression training with fully homomorphic encryption
BackgroundPrivacy-preserving computations on genomic data, and more generally on medical data, is a critical path technology for innovative,...
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Secure medical image encryption with Walsh–Hadamard transform and lightweight cryptography algorithm
It is important to ensure the privacy and security of the medical images that are produced with electronic health records. Security is ensured by...
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Logistic regression over encrypted data from fully homomorphic encryption
BackgroundOne of the tasks in the 2017 iDASH secure genome analysis competition was to enable training of logistic regression models over encrypted...
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Logistic regression model training based on the approximate homomorphic encryption
BackgroundSecurity concerns have been raised since big data became a prominent tool in data analysis. For instance, many machine learning algorithms...
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Semi-Parallel logistic regression for GWAS on encrypted data
BackgroundThe sharing of biomedical data is crucial to enable scientific discoveries across institutions and improve health care. For example,...
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Sociotechnical safeguards for genomic data privacy
Recent developments in a variety of sectors, including health care, research and the direct-to-consumer industry, have led to a dramatic increase in...
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Functional genomics data: privacy risk assessment and technological mitigation
The generation of functional genomics data by next-generation sequencing has increased greatly in the past decade. Broad sharing of these data is...
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Multimodal biomedical AI
The increasing availability of biomedical data from large biobanks, electronic health records, medical imaging, wearable and ambient biosensors, and...
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Treating medical data as a durable asset
Access to medical data is central for conducting research on genomics. However, to tap these metadata (observable traits and phenotypes, diagnoses...
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Federated Analysis of Neuroimaging Data: A Review of the Field
The field of neuroimaging has embraced sharing data to collaboratively advance our understanding of the brain. However, data sharing, especially...
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Secure searching of biomarkers through hybrid homomorphic encryption scheme
BackgroundAs genome sequencing technology develops rapidly, there has lately been an increasing need to keep genomic data secure even when stored in...
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Big data and deep learning for RNA biology
The exponential growth of big data in RNA biology (RB) has led to the development of deep learning (DL) models that have driven crucial discoveries....
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Exploring the Current State and Future Potential of Generative Artificial Intelligence Using a Generative Artificial Intelligence
Generative Artificial Intelligence (GAI) represents a paradigm shift within artificial intelligence, evolving beyond discriminative tasks to...
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Privacy challenges and research opportunities for genomic data sharing
The sharing of genomic data holds great promise in advancing precision medicine and providing personalized treatments and other types of...
