HARNESSING THE POWER OF AI AND MACHINE LEARNING FOR NEXT-GENERATION SEQUENCING DATA ANALYSIS: A COMPREHENSIVE REVIEW OF APPLICATIONS, CHALLENGES, AND FUTURE DIRECTIONS IN PRECISION ONCOLOGY

Resumo

This comprehensive review discusses the transformative impact of artificial intelligence (AI) and machine learning (ML) on next-generation sequencing (NGS) data analysis in precision oncology. AI and ML are pivotal in enhancing the precision of variant calling, annotating complex genomic data, discovering and validating new biomarkers, and integrating multi-omics data to elucidate cancer complexities. These technologies facilitate advanced clinical decision support systems that improve diagnostic accuracy and treatment efficacy. Despite these advancements, challenges persist, including the need for model interpretability, validation across diverse datasets, and integration into clinical practice. Future directions involve federated learning for data privacy, integration of multi-modal data, and expansion of explainable AI applications to enhance understanding and trust in AI-driven methodologies.