Longitudinal Biomarker Trajectories and Transition State Modelling: Machine Learning Approaches to Disease Progression Prediction and Clinical Staging
Keywords:
longitudinal biomarker trajectories, transition state modelling, machine learning approaches to disease progression prediction, clinical stagingAbstract
Introduction Disease progression prediction is a crucial part of the arsenal of tools available to healthcare providers. By annotating the future states of an individual according to a disease’s natural history, diagnosis and treatment decisions become much more efficient and effective. Biologically, diseases are typically driven by a complex interplay of genetic, lifestyle, and environmental factors that interact according to the disease context to determine disease initiation and progression.Downloads
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