BLOCKCHAIN CNN DEEP LEARNING EXPERT SYSTEM FOR HEALTHCARE EMERGENCY

Ricardo Carreã‘o Aguilera, Miguel Patiã‘o Ortiz, Adan Acosta Banda and Luis Enrique Carreã‘o Aguilera
Additional contact information
Ricardo Carreã‘o Aguilera: Universidad del Istmo, Ciudad Universitaria S/N, Barrio Santa Cruz, 4a. Sección Sto. Domingo Tehuantepec, C. P. 70760, Oaxaca, México
Miguel Patiã‘o Ortiz: ��Instituto Politécnico Nacional, SEPI ESIMEZ, Av. Luis Enrique Erro S/N, Unidad Profesional Adolfo López Mateos, Zacatenco, Alcaldía Gustavo A. Madero, C. P. 07738 Ciudad de México, México
Adan Acosta Banda: ��Instituto Politécnico Nacional, SEPI ESIMEZ, Av. Luis Enrique Erro S/N, Unidad Profesional Adolfo López Mateos, Zacatenco, Alcaldía Gustavo A. Madero, C. P. 07738 Ciudad de México, México
Luis Enrique Carreã‘o Aguilera: ��Instituto Politécnico Nacional, SEPI ESIMEZ, Av. Luis Enrique Erro S/N, Unidad Profesional Adolfo López Mateos, Zacatenco, Alcaldía Gustavo A. Madero, C. P. 07738 Ciudad de México, México

FRACTALS (fractals), 2021, vol. 29, issue 06, 1-10

Abstract: This paper relates to the field of Artificial Intelligence, specifically to image recognition, and provides an innovative method to take advantage of Blockchain Convolutional Neural Networks (BCNNs) in Emotion Recognitions (ERs) using audio–visual emotion patterns to determine a healthcare emergency to be attended. BCNN architectures were used to identify emergency patterns. The results obtained indicate that the proposed method is adequate for the classification and identification of audio–visual patterns using deep learning (DL) with Restricted Boltzmann Machines (RBMs). It is concluded that it is sufficient to consider the audio–visible key features obtained from the patient’s face and voice of the proposed model to recognize a healthcare emergency for immediate action. “Sense of urgency†and “with urgency but with self-control†are the emotion profiles considered for a healthcare emergency, and user personal emotion profiles are stored in the Blockchain ecosystem since they are deemed sensitive data.

Keywords: Blockchain Convolutional Neural Network (BCNN); Deep Learning (DL); Emotion Recognition (ER); Healthcare Emergency (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0218348X21502273
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:fracta:v:29:y:2021:i:06:n:s0218348x21502273

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0218348X21502273

Access Statistics for this article

FRACTALS (fractals) is currently edited by Tara Taylor

More articles in FRACTALS (fractals) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().