2018
DOI: 10.3390/magnetochemistry4030031
|View full text |Cite
|
Sign up to set email alerts
|

Supervised Learning to Predict Sperm Sorting by Magnetophoresis

Abstract: Machine learning is gaining popularity in the commercial world, but its benefits are yet to be well-utilised by many in the microfluidics community. There is immense potential in bridging the gap between applied engineering and artificial intelligence as well as statistics. We illustrate this by a case study investigating the sorting of sperm cells for assisted reproduction. Slender body theory (SBT) is applied to compute the behavior of sperm subjected to magnetophoresis, with due consideration given to stati… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
8
0

Year Published

2021
2021
2025
2025

Publication Types

Select...
4
2

Relationship

0
6

Authors

Journals

citations
Cited by 8 publications
(8 citation statements)
references
References 60 publications
0
8
0
Order By: Relevance
“…Chapter 2.1 and 2.3 is published as Koh JBY and Marcos (2015) The study of spermatozoa and sorting in relation to human reproduction. Microfluidics and Nanofluidics 18 (5)(6):755-774. DOI: 10.1007/s10404-014-1520-x.…”
Section: Authorship Attribution Statementmentioning
confidence: 99%
See 4 more Smart Citations
“…Chapter 2.1 and 2.3 is published as Koh JBY and Marcos (2015) The study of spermatozoa and sorting in relation to human reproduction. Microfluidics and Nanofluidics 18 (5)(6):755-774. DOI: 10.1007/s10404-014-1520-x.…”
Section: Authorship Attribution Statementmentioning
confidence: 99%
“…Chapter 6 is published as Koh JBY, Shen X and Marcos (2018) Supervised learning to predict sperm sorting by magnetophoresis. Magnetochemistry 4(3):31.…”
Section: Authorship Attribution Statementmentioning
confidence: 99%
See 3 more Smart Citations