Literature DB >> 34286422

Trending in human ARTs: Jumping on the Artificial Intelligence and Machine Learning bandwagon.

David F Albertini1.   

Abstract

Entities:  

Mesh：

Year:  2021        PMID： 34286422      PMCID： PMC8324736          DOI： 10.1007/s10815-021-02280-4

Source DB:  PubMed          Journal:  J Assist Reprod Genet        ISSN： 1058-0468            Impact factor:   3.357


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  8 in total

1.  Artificial intelligence: its applications in reproductive medicine and the assisted reproductive technologies.

Authors:  Nikica Zaninovic; Olivier Elemento; Zev Rosenwaks
Journal:  Fertil Steril       Date:  2019-07       Impact factor: 7.329

2.  Ethical limitations of algorithmic fairness solutions in health care machine learning.

Authors:  Melissa D McCradden; Shalmali Joshi; Mjaye Mazwi; James A Anderson
Journal:  Lancet Digit Health       Date:  2020-05

Review 3.  Are computational applications the "crystal ball" in the IVF laboratory? The evolution from mathematics to artificial intelligence.

Authors:  Mara Simopoulou; Konstantinos Sfakianoudis; Evangelos Maziotis; Nikolaos Antoniou; Anna Rapani; George Anifandis; Panagiotis Bakas; Stamatis Bolaris; Agni Pantou; Konstantinos Pantos; Michael Koutsilieris
Journal:  J Assist Reprod Genet       Date:  2018-07-27       Impact factor: 3.412

4.  From artefactual to artificial intelligence-meeting the needs of ART patients and practitioners.

Authors:  David F Albertini
Journal:  J Assist Reprod Genet       Date:  2018-09       Impact factor: 3.412

Review 5.  Artificial intelligence in human in vitro fertilization and embryology.

Authors:  Nikica Zaninovic; Zev Rosenwaks
Journal:  Fertil Steril       Date:  2020-11       Impact factor: 7.329

6.  Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization.

Authors:  Zev Rosenwaks; Olivier Elemento; Nikica Zaninovic; Iman Hajirasouliha; Pegah Khosravi; Ehsan Kazemi; Qiansheng Zhan; Jonas E Malmsten; Marco Toschi; Pantelis Zisimopoulos; Alexandros Sigaras; Stuart Lavery; Lee A D Cooper; Cristina Hickman; Marcos Meseguer
Journal:  NPJ Digit Med       Date:  2019-04-04

7.  Development of an artificial intelligence-based assessment model for prediction of embryo viability using static images captured by optical light microscopy during IVF.

Authors:  M VerMilyea; J M M Hall; S M Diakiw; A Johnston; T Nguyen; D Perugini; A Miller; A Picou; A P Murphy; M Perugini
Journal:  Hum Reprod       Date:  2020-04-28       Impact factor: 6.918

8.  Teasing out Artificial Intelligence in Medicine: An Ethical Critique of Artificial Intelligence and Machine Learning in Medicine.

Authors:  Mark Henderson Arnold
Journal:  J Bioeth Inq       Date:  2021-01-07       Impact factor: 2.216
  8 in total
  1 in total

1.  Machine Learning-Based Modeling of Ovarian Response and the Quantitative Evaluation of Comprehensive Impact Features.

Authors:  Liu Liu; Fujin Shen; Hua Liang; Zhe Yang; Jing Yang; Jiao Chen
Journal:  Diagnostics (Basel)       Date:  2022-02-14
  1 in total

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