FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3164199631> ?p ?o ?g. }

• W3164199631 endingPage "65" @default.
• W3164199631 startingPage "54" @default.
• W3164199631 abstract "Machine learning have been widely adopted in a variety of fields including engineering, science, and medicine revolutionizing how data is collected, used, and stored. Their implementation has led to a drastic increase in the number of computational models for the prediction of various numerical, categorical, or association events given input variables. We aim to examine recent advances in the use of machine learning when applied to the biomaterial field. Specifically, quantitative structure properties relationships offer the unique ability to correlate microscale molecular descriptors to larger macroscale material properties. These new models can be broken down further into four categories: regression, classification, association, and clustering. We examine recent approaches and new uses of machine learning in the three major categories of biomaterials: metals, polymers, and ceramics for rapid property prediction and trend identification. While current research is promising, limitations in the form of lack of standardized reporting and available databases complicates the implementation of described models. Herein, we hope to provide a snapshot of the current state of the field and a beginner's guide to navigating the intersection of biomaterials research and machine learning. Machine learning and its methods have found a variety of uses beyond the field of computer science but have largely been neglected by those in realm of biomaterials. Through the use of more computational methods, biomaterials development can be expediated while reducing the need for standard trial and error methods. Within, we introduce four basic models that readers can potentially apply to their current research as well as current applications within the field. Furthermore, we hope that this article may act as a “call to action” for readers to realize and address the current lack of implementation within the biomaterials field." @default.
• W3164199631 created "2021-06-07" @default.
• W3164199631 creator A5058157900 @default.
• W3164199631 creator A5061365281 @default.
• W3164199631 creator A5085942186 @default.
• W3164199631 date "2021-08-01" @default.
• W3164199631 modified "2023-10-12" @default.
• W3164199631 title "Machine learning and big data provide crucial insight for future biomaterials discovery and research" @default.
• W3164199631 cites W1505191356 @default.
• W3164199631 cites W1563270780 @default.
• W3164199631 cites W171147339 @default.
• W3164199631 cites W1973036367 @default.
• W3164199631 cites W1992985800 @default.
• W3164199631 cites W1993046136 @default.
• W3164199631 cites W1993236607 @default.
• W3164199631 cites W2017398555 @default.
• W3164199631 cites W2021630848 @default.
• W3164199631 cites W2024829861 @default.
• W3164199631 cites W2026899864 @default.
• W3164199631 cites W2033757486 @default.
• W3164199631 cites W2035831644 @default.
• W3164199631 cites W2036699652 @default.
• W3164199631 cites W2040062503 @default.
• W3164199631 cites W2040459007 @default.
• W3164199631 cites W2043767998 @default.
• W3164199631 cites W2046589863 @default.
• W3164199631 cites W2054286632 @default.
• W3164199631 cites W2054716083 @default.
• W3164199631 cites W2057767448 @default.
• W3164199631 cites W2074616700 @default.
• W3164199631 cites W2077727999 @default.
• W3164199631 cites W2078171026 @default.
• W3164199631 cites W2079604487 @default.
• W3164199631 cites W2081320283 @default.
• W3164199631 cites W2083780116 @default.
• W3164199631 cites W2085103117 @default.
• W3164199631 cites W2087985529 @default.
• W3164199631 cites W2090989512 @default.
• W3164199631 cites W2104780143 @default.
• W3164199631 cites W2114850508 @default.
• W3164199631 cites W2116924516 @default.
• W3164199631 cites W2118571345 @default.
• W3164199631 cites W2128245586 @default.
• W3164199631 cites W2129460449 @default.
• W3164199631 cites W2135964318 @default.
• W3164199631 cites W2142009706 @default.
• W3164199631 cites W2142480093 @default.
• W3164199631 cites W2147088528 @default.
• W3164199631 cites W2153693853 @default.
• W3164199631 cites W2159887157 @default.
• W3164199631 cites W2160697532 @default.
• W3164199631 cites W2161464748 @default.
• W3164199631 cites W2165259035 @default.
• W3164199631 cites W2171830166 @default.
• W3164199631 cites W2216412596 @default.
• W3164199631 cites W2267945123 @default.
• W3164199631 cites W2286211183 @default.
• W3164199631 cites W2290847742 @default.
• W3164199631 cites W2291908932 @default.
• W3164199631 cites W2318452386 @default.
• W3164199631 cites W2343106452 @default.
• W3164199631 cites W2464263270 @default.
• W3164199631 cites W2464725281 @default.
• W3164199631 cites W2467309505 @default.
• W3164199631 cites W2479160999 @default.
• W3164199631 cites W2490901606 @default.
• W3164199631 cites W2731593192 @default.
• W3164199631 cites W2742835787 @default.
• W3164199631 cites W2749580687 @default.
• W3164199631 cites W2753588101 @default.
• W3164199631 cites W2762272043 @default.
• W3164199631 cites W2767759168 @default.
• W3164199631 cites W2768638516 @default.
• W3164199631 cites W2780553247 @default.
• W3164199631 cites W2789575256 @default.
• W3164199631 cites W2791369768 @default.
• W3164199631 cites W2792196009 @default.
• W3164199631 cites W2797269284 @default.
• W3164199631 cites W2797648291 @default.
• W3164199631 cites W2801991413 @default.
• W3164199631 cites W2803775568 @default.
• W3164199631 cites W2883482411 @default.
• W3164199631 cites W2883528235 @default.
• W3164199631 cites W2884430236 @default.
• W3164199631 cites W2884901824 @default.
• W3164199631 cites W2887685819 @default.
• W3164199631 cites W2892439819 @default.
• W3164199631 cites W2893471587 @default.
• W3164199631 cites W2894634079 @default.
• W3164199631 cites W2895018811 @default.
• W3164199631 cites W2899070097 @default.
• W3164199631 cites W2899096831 @default.
• W3164199631 cites W2901223208 @default.
• W3164199631 cites W2903421796 @default.
• W3164199631 cites W2910642642 @default.
• W3164199631 cites W2910813586 @default.
• W3164199631 cites W2912452685 @default.
• W3164199631 cites W2921873493 @default.

• next