2021
DOI: 10.1042/bio_2021_168
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What do machines see? Utilizing artificial intelligence to explore cell biology

Abstract: With our ability to take and quantify numerous complex images of cells and cell populations, the ability to paint an accurate picture of the underlying data has never been more valuable. Deferring from the contemporary classics in data visualization to methods that exploit advances in artificial intelligence is an essential step in understanding high-throughput, three-dimensional microscopy data. This feature article discusses how generating or simulating representative cells that may not exist in the data set… Show more

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“…This, in turn, allows the assignment of data input to be continuous across classes rather than discrete. Cell morphology is a continuous variable with no two cells being identical in shape, but rather similar to each other or similar to exemplar shapes [35]. Therefore, describing cell shapes by a continuous similarity score to exemplar shapes offers a more natural solution than discrete binning into certain shape classes [26].…”
Section: Discussionmentioning
confidence: 99%
“…This, in turn, allows the assignment of data input to be continuous across classes rather than discrete. Cell morphology is a continuous variable with no two cells being identical in shape, but rather similar to each other or similar to exemplar shapes [35]. Therefore, describing cell shapes by a continuous similarity score to exemplar shapes offers a more natural solution than discrete binning into certain shape classes [26].…”
Section: Discussionmentioning
confidence: 99%