2018 - Member of the National Academy of Medicine (NAM)
Bradley A. Malin mostly deals with Computer security, Information privacy, Data mining, Data science and Artificial intelligence. His research integrates issues of Internet privacy and Medical record in his study of Computer security. Many of his research projects under Information privacy are closely connected to Genomics and Data sharing with Genomics and Data sharing, tying the diverse disciplines of science together.
His study in the field of Partition is also linked to topics like Data quality. His study in Data science is interdisciplinary in nature, drawing from both Social network analysis, Anomaly detection, Information Dissemination, Unsupervised learning and Information system. His Artificial intelligence study combines topics in areas such as Probability distribution and Machine learning.
Bradley A. Malin mainly investigates Data science, Data mining, Computer security, Information privacy and Health care. His Data science research is multidisciplinary, incorporating perspectives in Health informatics, Information sensitivity, Bioinformatics and Identification. His biological study spans a wide range of topics, including Record linkage, Diagnosis code, Machine learning and Artificial intelligence.
His Computer security study deals with Internet privacy intersecting with Confidentiality. Bradley A. Malin has researched Information privacy in several fields, including Secure multi-party computation and The Internet. His Health care study combines topics from a wide range of disciplines, such as Medical record, Information technology and Medical emergency.
Bradley A. Malin mainly focuses on Artificial intelligence, Data science, Data mining, Information privacy and Social media. His Artificial intelligence research includes themes of Odds ratio, Machine learning and Natural language processing. The concepts of his Data science study are interwoven with issues in Unsupervised learning and Task.
Bradley A. Malin combines subjects such as Diagnosis code and Divergence with his study of Data mining. His Information privacy study combines topics from a wide range of disciplines, such as Engineering ethics, Heuristic and Implementation. His Social media study integrates concerns from other disciplines, such as Data collection, Systematic review, Naive Bayes classifier, Mental health and Internet privacy.
The scientist’s investigation covers issues in Artificial intelligence, Information privacy, Data mining, Medical research and Deep learning. His Artificial intelligence study combines topics in areas such as Machine learning, Systematic review and Data collection. The various areas that Bradley A. Malin examines in his Information privacy study include Engineering ethics, Cost efficiency and Implementation.
Bradley A. Malin has included themes like Divergence and Scale in his Data mining study. His work blends Work and Data science studies together. His research in Data science intersects with topics in Informatics, Information technology, Health care and Privacy-enhancing technologies.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Preserving privacy by de-identifying face images
E.M. Newton;L. Sweeney;B. Malin.
IEEE Transactions on Knowledge and Data Engineering (2005)
A Systematic Review of Re-Identification Attacks on Health Data
Khaled El Emam;Elizabeth Jonker;Luk Arbuckle;Bradley Malin.
PLOS ONE (2011)
How (not) to protect genomic data privacy in a distributed network: using trail re-identification to evaluate and design anonymity protection systems
Bradley Malin;Latanya Sweeney.
Journal of Biomedical Informatics (2004)
Evaluating re-identification risks with respect to the HIPAA privacy rule
Kathleen Benitez;Bradley A. Malin.
Journal of the American Medical Informatics Association (2010)
Generating Multi-label Discrete Patient Records using Generative Adversarial Networks
Edward Choi;Siddharth Biswal;Bradley A. Malin;Jon Duke.
Machine Learning for Healthcare Conference (2017)
Privacy in the Genomic Era
Muhammad Naveed;Erman Ayday;Ellen W. Clayton;Jacques Fellay.
ACM Computing Surveys (2015)
Unsupervised Name Disambiguation via Social Network Similarity
Rubik: Knowledge Guided Tensor Factorization and Completion for Health Data Analytics
Yichen Wang;Robert Chen;Joydeep Ghosh;Joshua C. Denny.
knowledge discovery and data mining (2015)
A Cryptographic Approach to Securely Share and Query Genomic Sequences
M. Kantarcioglu;Wei Jiang;Ying Liu;B. Malin.
international conference of the ieee engineering in medicine and biology society (2008)
An evaluation of the current state of genomic data privacy protection technology and a roadmap for the future.
Bradley A. Malin.
Journal of the American Medical Informatics Association (2004)
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