| Title |
Selecting embryos with the highest implantation potential using data mining and decision tree based on classical embryo morphology and morphokinetics
|
|---|---|
| Published in |
Journal of Assisted Reproduction and Genetics, June 2017
|
| DOI | 10.1007/s10815-017-0955-x |
| Pubmed ID | |
| Authors |
Beatriz Carrasco, Gemma Arroyo, Yolanda Gil, Mª José Gómez, Ignacio Rodríguez, Pedro N. Barri, Anna Veiga, Montserrat Boada |
| Abstract |
The objective of this work was to determine which embryonic morphokinetic parameters up to D3 of in vitro development have predictive value for implantation for the selection of embryos for transfer in clinical practice based upon information generated from embryo transfers with known implantation data (KID). A total of 800 KID embryos (100% implantation rate (IR) per transfer and 0% IR per transfer) cultured in an incubator with Time-Lapse system were retrospectively analysed. Of them, 140 embryos implanted, whereas 660 did not. The analysis of morphokinetic parameters, together with the embryo morphology assessment on D3, enabled us to develop a hierarchical model that places the classical morphological score, the t4 and t8 morphokinetic values, as the variables with the best prognosis of implantation. In our decision tree, the classical morphological score is the most predictive parameter. Among embryos with better morphological scores, morphokinetics permits deselection of embryos with the lowest implantation potential. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 64 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 16% |
| Student > Bachelor | 9 | 14% |
| Student > Master | 8 | 13% |
| Student > Ph. D. Student | 7 | 11% |
| Other | 3 | 5% |
| Other | 7 | 11% |
| Unknown | 20 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 12 | 19% |
| Biochemistry, Genetics and Molecular Biology | 7 | 11% |
| Computer Science | 7 | 11% |
| Agricultural and Biological Sciences | 6 | 9% |
| Engineering | 5 | 8% |
| Other | 6 | 9% |
| Unknown | 21 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 June 2017.
All research outputs
#16,371,088
of 24,119,703 outputs
Outputs from Journal of Assisted Reproduction and Genetics
#963
of 1,697 outputs
Outputs of similar age
#203,291
of 320,149 outputs
Outputs of similar age from Journal of Assisted Reproduction and Genetics
#16
of 35 outputs
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