This paper is in the following e-collection/theme issue:

Drug Discovery and Clinical Trials (9) Biomedical Engineering Articles (2) Development and Evaluation of Research Methods, Instruments and Tools (769) Artificial Intelligence (2223)

Published on in Vol 5 (2026)

This is a member publication of Tulane University

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/81552, first published .
Accelerating Discovery of Leukemia Inhibitors Using AI-Driven Quantitative Structure-Activity Relationship: Algorithm Development and Validation

Accelerating Discovery of Leukemia Inhibitors Using AI-Driven Quantitative Structure-Activity Relationship: Algorithm Development and Validation

Accelerating Discovery of Leukemia Inhibitors Using AI-Driven Quantitative Structure-Activity Relationship: Algorithm Development and Validation

Authors of this article:

Samuel Kakraba1, 2 Author Orcid Image ;   Edmund Fosu Agyemang1 Author Orcid Image ;   Robert J Shmookler Reis3 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Samuel Kakraba   1, 2 , PhD ;   Edmund Fosu Agyemang   1 , MS ;   Robert J Shmookler Reis   3 , PhD

1 Biostatistics and Data Science, Celia Scott Weatherhead School of Public Health and Tropical Medicince, Tulane University, New Orleans, LA, United States

2 Tulane School of Medicine, Tulane Center for Aging, Tulane University, New Orleans, LA, United States

3 Department of Geriatrics, School of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, United States

Corresponding Author:

  • Samuel Kakraba, PhD
  • Biostatistics and Data Science
  • Celia Scott Weatherhead School of Public Health and Tropical Medicince
  • Tulane University
  • 1440 Canal Street
  • New Orleans, LA 70112
  • United States
  • Phone: 1 5049882475
  • Email: skakraba@tulane.edu