TY - GEN
T1 - Molecular Compounds Proposal for Drug-Resistant Tuberculosis in the Drug Discovery Process
AU - Campos, Michael Ramirez
AU - Rodriguez, Diana C.
AU - Orjuela-Canon, Alvaro D.
N1 - Funding Information:
ACKNOWLEDGMENT Authors acknowledge the support of the Universidad del Rosario for funding this project. In addition, the contribution of research incubator team Semillero en Inteligencia Artificial en Salud: Semill-IAS.
Publisher Copyright:
© 2023 IEEE.
PY - 2023/8/28
Y1 - 2023/8/28
N2 - Tuberculosis is a contagious disease considered as world emergency by the World Health Organization. One of the common prevalent problems are associated to drug-resistant TB, because of unsuccessful treatments of using antibiotics. The use of artificial intelligence algorithms, mainly machine learning (ML) models have allowed to provided more tools for the drug discovery field. For this study, the methodology used was driven to identify new components that may contribute to the inhibition of the inhA protein. Leveraging ML models that learn from data, six regression models were implemented. Best model obtained R2 value of 0.99 and a MSE value of 1.8 e-5.
AB - Tuberculosis is a contagious disease considered as world emergency by the World Health Organization. One of the common prevalent problems are associated to drug-resistant TB, because of unsuccessful treatments of using antibiotics. The use of artificial intelligence algorithms, mainly machine learning (ML) models have allowed to provided more tools for the drug discovery field. For this study, the methodology used was driven to identify new components that may contribute to the inhibition of the inhA protein. Leveraging ML models that learn from data, six regression models were implemented. Best model obtained R2 value of 0.99 and a MSE value of 1.8 e-5.
UR - http://www.scopus.com/inward/record.url?scp=85171617479&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85171617479&partnerID=8YFLogxK
U2 - 10.1109/ColCACI59285.2023.10225875
DO - 10.1109/ColCACI59285.2023.10225875
M3 - Conference contribution
AN - SCOPUS:85171617479
T3 - 2023 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2023 - Proceedings
SP - 1
EP - 5
BT - 2023 IEEE Colombian Conference on Applications of Computational Intelligence (ColCACI)
A2 - Orjuela-Canon, Alvaro David
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2023
Y2 - 26 July 2023 through 28 July 2023
ER -
