In conjunction with the IEEE International Conference on Bioinformatics and Biomedicine
Biomarkers-quantifiable signatures of biological processes-are the cornerstone of precision medicine. Ranging from molecular (e.g., genes, metabolites, noncoding RNAs) to digital (e.g., imaging-derived features), biomarkers serve critical roles in diagnostic (early disease detection), predictive (treatment response), and prognostic (disease trajectory). Their discovery, however, hinges on extracting actionable insights from complex, high-dimensional data, such as genomic sequences, proteomic interactions, and multimodal clinical datasets.
While advances in high-throughput technologies have generated vast biomarker-related data, traditional computational approaches often fall short in addressing noise, heterogeneity, and interpretability. This gap presents a unique opportunity for AI-driven innovation. Machine learning, deep learning, and probabilistic modeling are pushing boundaries in areas such as
The AI for Biomarker Discovery Conference is designed for computational biologists, AI researchers, and translational scientists to dissect cutting-edge methodologies, bridge algorithmic innovation with biological fidelity-addressing pitfalls like batch effects and dataset shift, and foster interdisciplinary collaboration to accelerate biomarkers from bench to bedside.
Join us in redefining the next frontier of biomarker discovery-where AI meets biological complexity with rigor, scalability, and impact.