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Fueled by breakthrough technology developments, the biological, biomedical,and behavioral sciences are now collecting more data than ever before. There isa critical need for time- and cost-efficient strategies to analyze andinterpret these data to advance human health. The recent rise of machinelearning as a powerful technique to integrate multimodality, multifidelitydata, and reveal correlations between intertwined phenomena presents a specialopportunity in this regard. However, classical machine learning techniquesoften ignore the fundamental laws of physics and result in ill-posed problemsor non-physical solutions. Multiscale modeling is a successful strategy tointegrate multiscale, multiphysics data and uncover mechanisms that explain theemergence of function. However, multiscale modeling alone often fails toefficiently combine large data sets from different sources and different levelsof resolution. We show how machine learning and multiscale modeling cancomplement each other to create robust predictive models that integrate theunderlying physics to manage ill-posed problems and explore massive designspaces. We critically review the current literature, highlight applications andopportunities, address open questions, and discuss potential challenges andlimitations in four overarching topical areas: ordinary differential equations,partial differential equations, data-driven approaches, and theory-drivenapproaches. Towards these goals, we leverage expertise in applied mathematics,computer science, computational biology, biophysics, biomechanics, engineeringmechanics, experimentation, and medicine. Our multidisciplinary perspectivesuggests that integrating machine learning and multiscale modeling can providenew insights into disease mechanisms, help identify new targets and treatmentstrategies, and inform decision making for the benefit of human health.

npj digital medicine

Integrating Machine Learning and Multiscale Modeling: Perspectives,  Challenges, and Opportunities in the Biological, Biomedical, and Behavioral  Sciences