Provider > Data Privacy

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  Detect PHI for Deidentification

  • Published on: March, 2021
  • John Snow Labs
  • Code Available

  Named Entity recognition annotator allows for a generic model to be trained by utilizing a deep learning algorithm (Char CNNs - BiLSTM - CRF - word em ...

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  Differentially Private Synthetic Data-Applied Evaluations and Enhancements

  • Published on: March, 2020
  • Samira Pouyanfar, Anuj Desai, Eduardo de Leon, Joshua Allen, Lucas Rosenblatt, Xiaoyan Liu
  • Code Available

  When collecting sensitive information from groups or organization, it is highly important to maintain an individual's privacy. A formalization of priv ...

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  Generating Multi-label Discrete Patient Records using Generative Adversarial Networks

  • Published on: January, 2018
  • Siddharth Biswal, Edward Choi, Walter F. Stewart, Bradley Malin, Jimeng Sun, Jon Duke
  • Code Available

  Researchers have a controlled access to the Electronic Health Records (EHR) data as it is composed of personal identifiers and sensitive medical info ...

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  RIDDLE-Race and Ethnicity Imputation From Disease History with Deep Learning

  • Published on: April, 2018
  • Xin Gao, Andrey Rzhetsky, Ji-Sung Kim
  • Code Available

  Electronic medical records that have been anonymized are becoming a more popular source of research data. However, these datasets frequently lack info ...

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  Generating Synthetic Training Data for Supervised De-Identification of Electronic Health Records

  • Published on: May, 2021
  • Christin Seifert, Jan Trienes, Claudia Alessandra Libbi, Dolf Trieschnigg
  • Code Available

  Synthetic data presents a promising solution to the privacy concern, if synthetic data has comparable utility to real data and if it preserves the pri ...

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  CorGAN-Correlation Capturing Convolutional Neural Networks for Generating Synthetic Healthcare Records

  • Published on: February, 2020
  • Edward A. Fox, Amirsina Torfi
  • Code Available

  In healthcare domain, researchers face a lot of privacy challenges when it comes to create a deep learning model using electronic health record (EHR) ...

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  Data Shapley-Equitable Valuation of Data for Machine Learning

  • Published on: June, 2019
  • James Zou, Amirata Ghorbani
  • Code Available

  In healthcare markets, it has been suggested that individuals should be compensated for the data that they generate, but equitable valuation for indiv ...

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  The Medkit-Learning Environment-Medical Decision Modelling through Simulation

  • Published on: June, 2021
  • Alex J. Chan, Alihan Hüyük, Ioana Bica, Mihaela van der Schaar, Daniel Jarett
  • Code Available

  Medkit is a new benchmarking suite designed specifically for medical sequential decision making. The models produces batch dataset, which can be used ...

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  GAIN-Missing Data Imputation using Generative Adversarial Nets

  • Published on: January, 2018
  • Mihaela van der Schaar, James Jordon, Jinsung Yoon
  • Code Available

  GAIN comprises of a method for imputing missing data by adapting the Generative Adversarial Nets (GAN) framework. GAN models consists of generator and ...

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  Differentially Private Synthetic Medical Data Generation using Convolutional GANs

  • Published on: December, 2020
  • Chandan K. Reddy, Edward A. Fox, Amirsina Torfi
  • Code Available

  Torfi et. al. have built a privacy-preserving GAN model using Renyi differential privacy for generating synthetic medical data from real health record ...