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In addition to tumor volume calculation, accurate automatic segmentation methods additionally have the potential to reduce the variability and increase the standardization of other measurements and protocols, including the quantification of edema or necrosis.
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Both methods result in a rough sculpture with sprues and vents still attached; the direct method additionally has the wire skeleton and inner core inside, while the indirect method only has the inner core material present.
Additionally, methods have been presented that separate absorption and scattering contributions [ 18, 19] which may help lead to determination of absorber concentration within tissues.
Additionally, other methods have been developed for single cell epigenomic sequencing, such as Hi-C methods that characterize chromatin interactions in the genome of single cells [9], and single chromatin molecule analysis at the nanoscale (SCAN) that extracts single chromatin with fluorescent antibodies through fluidic channels [72].
Additionally, computational methods have been developed to suggest different types of genetic modifications (e.g. gene deletion/addition or up/down regulation), as well as suggest strategies meeting different criteria (e.g. high yield, high productivity, or substrate co-utilization).
Additionally, these methods have been successfully embedded into robot systems.
Additionally, various methods have been proposed to optimize the properties of CVD graphene[10 14].
Additionally, analytical methods have been developed to compute reduced loading capacity of bridge sections with deteriorated steel beams (Van de Lindt et al. 2005).
Additionally, DASH methods have difficulty in handling live video stream as it converts the video data into several chunks and encodes at different quality level to be downloaded by the receiver judiciously [7].
Additionally, many methods have been developed for detecting DMCs based on a variety of probability models [ 13- 15].
Additionally, computational methods have been developed to identify differentially methylated regions for specific DNA methylation platforms (Aryee et al., 2014; Wang et al., 2012; Warden et al., 2013).
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