Optimized explainable AI and digital twin for patient flow improvement in ICU during respiratory epidemics
Miguel Ortiz-Barrios, Sebastián Arias-Fonseca, Helder Jose Celani de Souza, Jose F Torres-Avila, Ana Maldonado-Olea, Isidro J Ángel-Gaviria, Tobías A Parodi-Camano, Omar Ayala Ruiz, Lorena del Jesus Sarao-Cruz, Martha María Sánchez-Bolívar · 2026
Read Optimized explainable AI and digital twin for patient flow improvement in ICU during respiratory epidemics by Miguel Ortiz-Barrios, Sebastián Arias-Fonseca, Helder Jose Celani de Souza, Jose F Torres-Avila, Ana Maldonado-Olea, Isidro J Ángel-Gaviria, Tobías A Parodi-Camano, Omar Ayala Ruiz, Lorena del Jesus Sarao-Cruz, Martha María Sánchez-Bolívar (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13285456.txt.
Description
During a respiratory epidemic an intensive care unit must guess who arrives next, or patients wait in the emergency ward. A ten-author team builds a decision aid in 2026 that pairs explainable AI with a digital twin of the unit. A boosting model predicts each emergency patient's chance of transfer to intensive care within a day. Bayesian tuning sharpens it. The twin then plays out the coming load and tests fixes for the bottlenecks it finds.
In a European hospital group the predictor proved careful: about 95 percent specific and 82 percent sensitive. A transfer deal with a partner hospital cut median bed waiting to roughly 67 to 69 hours. The authors present the pairing as practical epidemic planning.
Catalog record
| CREATOR | Miguel Ortiz-Barrios, Sebastián Arias-Fonseca, Helder Jose Celani de Souza, Jose F Torres-Avila, Ana Maldonado-Olea, Isidro J Ángel-Gaviria, Tobías A Parodi-Camano, Omar Ayala Ruiz, Lorena del Jesus Sarao-Cruz, Martha María Sánchez-Bolívar |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 80 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |