@article{737566,
      recid = {737566},
      author = {Gkoulalas-Divanis, Aris, and Loukides, Grigorios,},
      title = {Medical data privacy handbook [electronic resource] /},
      pages = {1 online resource},
      note = {Includes index.},
      abstract = {This handbook covers Electronic Medical Record (EMR)  systems, which enable the storage, management, and sharing  of massive amounts of demographic, diagnosis, medication,  and genomic information. It presents privacy-preserving  methods for medical data, ranging from laboratory test  results to doctors' comments. The reuse of EMR data can  greatly benefit medical science and practice, but must be  performed in a privacy-preserving way according to data  sharing policies and regulations. Written by world-renowned  leaders in this field, each chapter offers a survey of a  research direction or a solution to problems in established  and emerging research areas. The authors explore scenarios  and techniques for facilitating the anonymization of  different types of medical data, as well as various data  mining tasks. Other chapters present methods for emerging  data privacy applications and medical text  de-identification, including detailed surveys of deployed  systems. A part of the book is devoted to legislative and  policy issues, reporting on the US and EU privacy  legislation and the cost of privacy breaches in the  healthcare domain. This reference is intended for  professionals, researchers and advanced-level students  interested in safeguarding medical data.},
      url = {http://library.usi.edu/record/737566},
      doi = {https://doi.org/10.1007/978-3-319-23633-9},
}