Machine Learning Insights into Antimicrobial Efficacy and Resistance

Explore cutting-edge applications of machine learning in addressing antimicrobial resistance through this 34-minute webinar presented by Dr. Jason H. Yang, Assistant Professor and Chancellor Scholar at Rutgers New Jersey Medical School. Gain insights into how mathematical models, machine learning, and bioinformatic approaches combined with experimental techniques are being used to study and combat antimicrobial resistance. Learn about recent innovations poised to overcome obstacles in understanding, diagnosing, and treating this pressing global health challenge. Discover how systems and synthetic biology research is advancing the fight against tuberculosis and developing immune cell therapies. Earn PACE credits by watching the webinar and following the provided instructions. Connect with Labroots on various social media platforms for more scientific content and updates.

Machine Learning Insights into Antimicrobial Efficacy and Resistance