@inproceedings{5dc8a0026fce4f91bc54cf7fdc4a0810,
title = "Technological model of facial recognition for the identification of patients in the health sector",
abstract = "The identification of patients within medical institutions is an important issue to provide better care in health centers and avoid identity personifications. The risk of medical identity theft is one important factor for patient safety. Technologies are improving, such as fingerprints, atrial biometry or electrocardiograms to improve safety measures. However, biometric counterfeiting methods have increased and violated the security of these technological models. This article proposes a technological model of facial recognition to efficiently identify patients according to cognitive services in medical centers. The technological model was implemented in the UROGINEC clinic for the proof of concept. The results of the identification of the patient were successful with a precision percentage of 95.82 in an average of 3 s. This allowed the clinic to prevent identity theft with alert messages and improved the user experience within the medical institution.",
keywords = "Biometrics, Cloud computing, Facial recognition, Health sector, Information systems, Patient identification",
author = "\{La Madrid\}, Diego and Mart{\'i}n Barriga and Pedro Shiguihara",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 4th Brazilian Technology Symposium, BTSym 2018 ; Conference date: 23-10-2018 Through 25-10-2018",
year = "2019",
doi = "10.1007/978-3-030-16053-1\_58",
language = "Ingl{\'e}s",
isbn = "9783030160524",
series = "Smart Innovation, Systems and Technologies",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "595--603",
editor = "Yuzo Iano and Loschi, \{Hermes Jos{\'e}\} and Rangel Arthur and Osamu Saotome and \{Vieira Estrela\}, V{\^a}nia",
booktitle = "Proceedings of the 4th Brazilian Technology Symposium (BTSym{\textquoteright}18) - Emerging Trends and Challenges in Technology",
}