WormSpot: a machine learning-powered viability scoring platform in C. elegans for Candida pathogenicity studies

Puntos clave

• To develop WormSpot, a machine learning platform that scores viability in C. elegans for studying Candida pathogenicity and antifungal resistance.
• Utilized machine learning algorithms to assess C. elegans viability in the presence of Candida.
• Conducted high-throughput screening for antifungal efficacy.
• Established infection models to evaluate virulence.
• Demonstrated effective scoring of C. elegans viability with machine learning in antifungal studies.
• Achieved significant improvements in pathogen phenotyping efficiency.
• Provided robust data supporting antifungal compound screening in high-throughput settings.