Análisis de Datos COVID-19 Utilizando Algoritmos de Inteligencia Artificial
- A. Elda Y. Martinez-Escobar,
- B. Jose M. Celaya-Padilla,
- ,
- C. Ireri A. Sustaita-Torres,
- Manuel A. Murillo-Soto,
- Jorge I. Galvan-Tejada
- Universidad Autonoma de Zacatecas,
Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
Sustainable Development Goals
SDG 3 Good Health and Well
Publication metrics
Metrics
SciVal
Author count
6
SciVal
Paper percentile
22
Abstract
The COVID-19 pandemic has markedly catalyzed the advancement of innovative tools. With the aim of crafting resilient predictive models, an extensive training process has been executed to anticipate the risk of mortality or survival associated with the categories of moderate/severe hospitalization and critical patient cases.
Publication Information
Output type
Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
Original language
EnglishPublication milestones
- Published - 2023
Publication status
Published - 2023
Publisher
Institute of Electrical and Electronics Engineers Inc., United StatesPublication series
- Publication series name: 2023 IEEE EMBS R9 Conference, EMBS R9 2023
ISBN (Electronic)
9798350381092Publication IDs
- Scopus: 85193973752
Host publication title
2023 IEEE EMBS R9 Conference, EMBS R9 2023Related Event
Title
2023 IEEE EMBS R9 Conference, EMBS R9 2023
Event type
ConferenceDate
05/10/2023 - 07/10/2023Location
GuadalajaraMexico