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 the amount of genomic data that …
to-consumer industry, have led to a dramatic increase in the amount of genomic data that …
Federated learning in a medical context: a systematic literature review
Data privacy is a very important issue. Especially in fields like medicine, it is paramount to
abide by the existing privacy regulations to preserve patients' anonymity. However, data is …
abide by the existing privacy regulations to preserve patients' anonymity. However, data is …
[PDF][PDF] PATE-GAN: Generating synthetic data with differential privacy guarantees
Machine learning has the potential to assist many communities in using the large datasets
that are becoming more and more available. Unfortunately, much of that potential is not …
that are becoming more and more available. Unfortunately, much of that potential is not …
Generating multi-label discrete patient records using generative adversarial networks
Access to electronic health record (EHR) data has motivated computational advances in
medical research. However, various concerns, particularly over privacy, can limit access to …
medical research. However, various concerns, particularly over privacy, can limit access to …
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 interventions. However, these …
providing personalized treatments and other types of interventions. However, these …
Anonymization through data synthesis using generative adversarial networks (ads-gan)
The medical and machine learning communities are relying on the promise of artificial
intelligence (AI) to transform medicine through enabling more accurate decisions and …
intelligence (AI) to transform medicine through enabling more accurate decisions and …
Privacy-preserving generative deep neural networks support clinical data sharing
Background: Data sharing accelerates scientific progress but sharing individual-level data
while preserving patient privacy presents a barrier. Methods and Results: Using pairs of …
while preserving patient privacy presents a barrier. Methods and Results: Using pairs of …
[كتاب][B] Data Science for Business: What you need to know about data mining and data-analytic thinking
F Provost, T Fawcett - 2013 - books.google.com
Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for
Business introduces the fundamental principles of data science, and walks you through the" …
Business introduces the fundamental principles of data science, and walks you through the" …
The PII problem: Privacy and a new concept of personally identifiable information
THE P11 PROBLEM: PRIVACY AND A NEW CONCEPT OF PERSONALLY IDENTIFIABLE
INFORMATION Page 1 THE P11 PROBLEM: PRIVACY AND A NEW CONCEPT OF …
INFORMATION Page 1 THE P11 PROBLEM: PRIVACY AND A NEW CONCEPT OF …
Robust de-anonymization of large sparse datasets
We present a new class of statistical de-anonymization attacks against high-dimensional
micro-data, such as individual preferences, recommendations, transaction records and so …
micro-data, such as individual preferences, recommendations, transaction records and so …