2021
DOI: 10.1002/adma.202102703
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Machine Learning‐Driven Biomaterials Evolution

Abstract: Biomaterials is an exciting and dynamic field, which uses a collection of diverse materials to achieve desired biological responses. While there is constant evolution and innovation in materials with time, biomaterials research has been hampered by the relatively long development period required. In recent years, driven by the need to accelerate materials development, the applications of machine learning in materials science has progressed in leaps and bounds. The combination of machine learning with high‐thro… Show more

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Cited by 113 publications
(76 citation statements)
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“…It is possible to estimate the potential biocompatibility of 2D materials using machine-learning-driven simulation and calculation on biomaterials' design and hazard reduction. [1151][1152][1153][1154][1155] What matters is whether or not 2D materials can be shown to be safe for humans to use in vivo so that the ambiguity in the biocompatibility of 2D materials may be clarified. [475] 3) Making 2D materials-based wearable energy harvesters more efficient and effective.…”
Section: Discussionmentioning
confidence: 99%
“…It is possible to estimate the potential biocompatibility of 2D materials using machine-learning-driven simulation and calculation on biomaterials' design and hazard reduction. [1151][1152][1153][1154][1155] What matters is whether or not 2D materials can be shown to be safe for humans to use in vivo so that the ambiguity in the biocompatibility of 2D materials may be clarified. [475] 3) Making 2D materials-based wearable energy harvesters more efficient and effective.…”
Section: Discussionmentioning
confidence: 99%
“…Moreover, it is estimated that, in the near future, personalized prosthetic biomaterials could be developed and improved, based on the important acquisition of data at the individual level (biomarkers), including at the salivary level [ 15 , 137 ]. Furthermore, the application of machine learning in material science will allow the acceleration of development in biomaterial manufacturing [ 138 ].…”
Section: Definitive Prosthetic Materials Used For Obtaining Oral Impl...mentioning
confidence: 99%
“…Polymer development is largely based on an iterative process which requires significant resources, time and intuition. Increasingly, the field is developing machine-learning tools to predict properties of polymers in-silico ( 59 ). This data-driven approach may enable rational polymer design based on the required function in the tissue type the polymer interacts with.…”
Section: Translational Hurdlesmentioning
confidence: 99%