Predicting Calcein Release from Ultrasound-Targeted Liposomes: A Comparative Analysis of Random Forest and Support Vector Machine.

Journal: Technology in cancer research & treatment

PMID: 39539114

Abstract

OBJECTIVE: This study presents a comparative analysis of RF and SVM for predicting calcein release from ultrasound-triggered, targeted liposomes under varied low-frequency ultrasound (LFUS) power densities (6.2, 9, and 10 mW/cm).

Authors

Ibrahim Shomope

Department of Chemical and Biological Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates.
Kelly M Percival

Department of Chemical and Biological Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates.
Nabil M Abdel Jabbar

Department of Chemical and Biological Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates.
Ghaleb A Husseini

Keywords

Drug Delivery Systems Drug Liberation Fluoresceins Humans Liposomes Random Forest Support Vector Machine Ultrasonic Waves

External Resources

View on PubMed Access via DOI PubMed (39539114)

Predicting Calcein Release from Ultrasound-Targeted Liposomes: A Comparative Analysis of Random Forest and Support Vector Machine.

Abstract

Authors

Keywords

External Resources

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