AIMC Topic: Confidentiality

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A Method of Information Protection for Collaborative Deep Learning under GAN Model Attack.

IEEE/ACM transactions on computational biology and bioinformatics Jun 3, 2021
Deep learning is widely used in the medical field owing to its high accuracy in medical image classification and biological applications. However, under collaborative deep learning, there is a serious risk of information leakage based on the deep con...
Deep Learning Computational Biology Confidentiality Computer Security Humans Neural Networks, Computer
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Swarm Learning for decentralized and confidential clinical machine learning.

Nature May 26, 2021
Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes. However, there is an i...
Tuberculosis Datasets as Topic Leukemia Leukocytes Confidentiality Lung Diseases Software Blockchain COVID-19 Precision Medicine Male Disease Outbreaks Clinical Decision-Making Female Humans Machine Learning
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How US law will evaluate artificial intelligence for covid-19.

BMJ (Clinical research ed.) Mar 15, 2021
explore the legal implications of using artificial intelligence in the response to covid-19 and call for more robust evaluation frameworks
COVID-19 SARS-CoV-2 Risk Assessment United States Humans Artificial Intelligence Machine Learning Social Discrimination Confidentiality Health Insurance Portability and Accountability Act Personally Identifiable Information
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VANTAGE6: an open source priVAcy preserviNg federaTed leArninG infrastructurE for Secure Insight eXchange.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
Answering many of the research questions in the field of cancer informatics requires incorporating and centralizing data that are hosted by different parties. Federated Learning (FL) has emerged as a new approach in which a global model can be genera...
Confidentiality Humans Privacy Machine Learning Learning
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Secure and Robust Machine Learning for Healthcare: A Survey.

IEEE reviews in biomedical engineering Jan 22, 2021
Recent years have witnessed widespread adoption of machine learning (ML)/deep learning (DL) techniques due to their superior performance for a variety of healthcare applications ranging from the prediction of cardiac arrest from one-dimensional heart...
Electronic Health Records Diagnosis, Computer-Assisted Confidentiality Humans Machine Learning
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Big data in epilepsy: Clinical and research considerations. Report from the Epilepsy Big Data Task Force of the International League Against Epilepsy.

Epilepsia Aug 7, 2020
Epilepsy is a heterogeneous condition with disparate etiologies and phenotypic and genotypic characteristics. Clinical and research aspects are accordingly varied, ranging from epidemiological to molecular, spanning clinical trials and outcomes, gene...
Research Support as Topic Neuroimaging Computer Security Stakeholder Participation Electrocorticography Societies, Medical Common Data Elements Information Dissemination Advisory Committees Biological Ontologies Epilepsy Confidentiality Telemedicine Electronic Health Records Biomedical Research Deep Learning Smartphone Genomics Big Data Wearable Electronic Devices Humans Brain
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Exploring the Privacy-Preserving Properties of Word Embeddings: Algorithmic Validation Study.

Journal of medical Internet research Jul 15, 2020
BACKGROUND: Word embeddings are dense numeric vectors used to represent language in neural networks. Until recently, there had been no publicly released embeddings trained on clinical data. Our work is the first to study the privacy implications of r...
Confidentiality Humans Algorithms Natural Language Processing
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Machine Learning Systems Applied to Health Data and System.

European journal of health law May 19, 2020
The use of machine learning (ML) in medicine is becoming increasingly fundamental to analyse complex problems by discovering associations among different types of information and to generate knowledge for medical decision support. Many regulatory and...
Safety Medical Informatics Medical Device Legislation Bias Confidentiality Malpractice Humans Machine Learning Drug Discovery Drug Development Decision Making Risk Management Software Precision Medicine Trust
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Active deep learning to detect demographic traits in free-form clinical notes.

Journal of biomedical informatics May 16, 2020
The free-form portions of clinical notes are a significant source of information for research, but before they can be used, they must be de-identified to protect patients' privacy. De-identification efforts have focused on known identifier types (nam...
Humans Phenotype Deep Learning Confidentiality Problem-Based Learning Demography
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Ethics and governance for digital disease surveillance.

Science (New York, N.Y.) May 11, 2020
Pneumonia, Viral Coronavirus Infections Datasets as Topic Epidemiological Monitoring Artificial Intelligence Machine Learning Humans Pandemics COVID-19 Forecasting Confidentiality
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