AI in Biomarker Research
This session explores the application of artificial intelligence, machine learning, and computational methods to biomarker discovery and validation. Researchers are invited to submit abstracts involving predictive algorithms, automated data analysis, pattern recognition, and computational modelling. Relevant fields include bioinformatics, data science, computational biology, biomedical engineering, clinical informatics, and precision medicine. Suitable topics include machine-learning models for disease prediction, AI-based biomarker identification, analysis of genomic and proteomic datasets, and integration of clinical and molecular information. Studies assessing algorithm accuracy, model interpretability, reproducibility, and clinical performance are welcome. Research using deep learning, statistical learning, and large-scale biomedical datasets is also relevant. Contributions should demonstrate how computational approaches can improve biomarker discovery, patient classification, diagnostic accuracy, or personalized treatment planning.
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AI in Biomarker Research Conference Speakers
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