Medical decision support system using weakly-labeled lung CT scans

ABSTRACT: Purpose: Determination and development of an effective set of models leveraging Artificial Intelligence techniques to generate a system able to support clinical practitioners working with COVID-19 patients. It involves a pipeline including classification, lung and lesion segmentation, as w...

Full description

Autores:

Mejía Velásquez, Marcia
Tavera Gallego, Fabby Maritza
Murillo González, Alejandro
González González, David
Jaramillo Duque, Laura
Galeano Ruiz, Carlos Andrés
Hernández Arango, Alejandro
Restrepo Rivera, David
Paniagua Castrillón, Juan Guillermo
Ariza Jiménez, Leandro
Garcés Echeverri, José Julián
Diaz León, Christian Andrés
Serna Higuita, Diana Lucia
Barrios Bustamante, Wayner
Arrázola Lara, Wiston
Mejía Mejía, Miguel Angel
Marín Ramírez, Daniela
Arango Mejía, Sebastián
Salinas Miranda, Emmanuel
Quintero Montoya, Olga Lucía

Tipo de recurso:

Tesis

Fecha de publicación:

2022

Institución:

Universidad de Antioquia

Repositorio:

Repositorio UdeA

Idioma:

eng

OAI Identifier:

oai:bibliotecadigital.udea.edu.co:10495/39951

Acceso en línea:

https://hdl.handle.net/10495/39951
https://www.frontiersin.org/articles/10.3389/fmedt.2022.980735/full

Palabra clave:

Lung
Pulmón
Lung diseases
Enfermedades pulmonares
COVID-19
Tomography
Tomografía
Machine learning
Aprendizaje automático
Supervised machine learning
Aprendizaje automático supervisado
Decision making
Toma de decisiones
Weak-labels
Image segmentation
https://id.nlm.nih.gov/mesh/D008168
https://id.nlm.nih.gov/mesh/D008171
https://id.nlm.nih.gov/mesh/D000086382
https://id.nlm.nih.gov/mesh/D014054
https://id.nlm.nih.gov/mesh/D000069550
https://id.nlm.nih.gov/mesh/D000069553
https://id.nlm.nih.gov/mesh/D003657

Rights

openAccess

License

https://creativecommons.org/licenses/by-nc-sa/4.0/