Literature DB >> 32989510

AI in the treatment of fertility: key considerations.

Jason Swain1, Matthew Tex VerMilyea2, Marcos Meseguer3, Diego Ezcurra4.   

Abstract

Artificial intelligence (AI) has been proposed as a potential tool to help address many of the existing problems related with empirical or subjective assessments of clinical and embryological decision points during the treatment of infertility. AI technologies are reviewed and potential areas of implementation of algorithms are discussed, highlighting the importance of following a proper path for the development and validation of algorithms, including regulatory requirements, and the need for ecosystems containing enough quality data to generate it. As evidenced by the consensus of a group of experts in fertility if properly developed, it is believed that AI algorithms may help practitioners from around the globe to standardize, automate, and improve IVF outcomes for the benefit of patients. Collaboration is required between AI developers and healthcare professionals to make this happen.

Entities:  

Keywords:  AI; algorithms; embryos; fertility

Mesh:

Year:  2020        PMID: 32989510      PMCID: PMC7642046          DOI: 10.1007/s10815-020-01950-z

Source DB:  PubMed          Journal:  J Assist Reprod Genet        ISSN: 1058-0468            Impact factor:   3.412


  36 in total

1.  Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists.

Authors:  H A Haenssle; C Fink; R Schneiderbauer; F Toberer; T Buhl; A Blum; A Kalloo; A Ben Hadj Hassen; L Thomas; A Enk; L Uhlmann
Journal:  Ann Oncol       Date:  2018-08-01       Impact factor: 32.976

2.  Classification of the Clinical Images for Benign and Malignant Cutaneous Tumors Using a Deep Learning Algorithm.

Authors:  Seung Seog Han; Myoung Shin Kim; Woohyung Lim; Gyeong Hun Park; Ilwoo Park; Sung Eun Chang
Journal:  J Invest Dermatol       Date:  2018-02-08       Impact factor: 8.551

3.  Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks.

Authors:  James M Brown; J Peter Campbell; Andrew Beers; Ken Chang; Susan Ostmo; R V Paul Chan; Jennifer Dy; Deniz Erdogmus; Stratis Ioannidis; Jayashree Kalpathy-Cramer; Michael F Chiang
Journal:  JAMA Ophthalmol       Date:  2018-07-01       Impact factor: 7.389

4.  Dermatologist-level classification of skin cancer with deep neural networks.

Authors:  Andre Esteva; Brett Kuprel; Roberto A Novoa; Justin Ko; Susan M Swetter; Helen M Blau; Sebastian Thrun
Journal:  Nature       Date:  2017-01-25       Impact factor: 49.962

5.  Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy.

Authors:  Pu Wang; Xiao Xiao; Jeremy R Glissen Brown; Tyler M Berzin; Mengtian Tu; Fei Xiong; Xiao Hu; Peixi Liu; Yan Song; Di Zhang; Xue Yang; Liangping Li; Jiong He; Xin Yi; Jingjia Liu; Xiaogang Liu
Journal:  Nat Biomed Eng       Date:  2018-10-10       Impact factor: 25.671

6.  Automated Grading of Age-Related Macular Degeneration From Color Fundus Images Using Deep Convolutional Neural Networks.

Authors:  Philippe M Burlina; Neil Joshi; Michael Pekala; Katia D Pacheco; David E Freund; Neil M Bressler
Journal:  JAMA Ophthalmol       Date:  2017-11-01       Impact factor: 7.389

7.  Real-Time Use of Artificial Intelligence in Identification of Diminutive Polyps During Colonoscopy: A Prospective Study.

Authors:  Yuichi Mori; Shin-Ei Kudo; Masashi Misawa; Yutaka Saito; Hiroaki Ikematsu; Kinichi Hotta; Kazuo Ohtsuka; Fumihiko Urushibara; Shinichi Kataoka; Yushi Ogawa; Yasuharu Maeda; Kenichi Takeda; Hiroki Nakamura; Katsuro Ichimasa; Toyoki Kudo; Takemasa Hayashi; Kunihiko Wakamura; Fumio Ishida; Haruhiro Inoue; Hayato Itoh; Masahiro Oda; Kensaku Mori
Journal:  Ann Intern Med       Date:  2018-08-14       Impact factor: 25.391

8.  Fast and accurate view classification of echocardiograms using deep learning.

Authors:  Ali Madani; Ramy Arnaout; Mohammad Mofrad; Rima Arnaout
Journal:  NPJ Digit Med       Date:  2018-03-21

9.  Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning.

Authors:  Nicolas Coudray; Paolo Santiago Ocampo; Theodore Sakellaropoulos; Navneet Narula; Matija Snuderl; David Fenyö; Andre L Moreira; Narges Razavian; Aristotelis Tsirigos
Journal:  Nat Med       Date:  2018-09-17       Impact factor: 53.440

10.  Fully Automated Echocardiogram Interpretation in Clinical Practice.

Authors:  Jeffrey Zhang; Sravani Gajjala; Pulkit Agrawal; Geoffrey H Tison; Laura A Hallock; Lauren Beussink-Nelson; Mats H Lassen; Eugene Fan; Mandar A Aras; ChaRandle Jordan; Kirsten E Fleischmann; Michelle Melisko; Atif Qasim; Sanjiv J Shah; Ruzena Bajcsy; Rahul C Deo
Journal:  Circulation       Date:  2018-10-16       Impact factor: 29.690

View more
  6 in total

Review 1.  Automation in ART: Paving the Way for the Future of Infertility Treatment.

Authors:  Kadrina Abdul Latif Abdullah; Tomiris Atazhanova; Alejandro Chavez-Badiola; Sourima Biswas Shivhare
Journal:  Reprod Sci       Date:  2022-08-03       Impact factor: 2.924

2.  Correlation between an annotation-free embryo scoring system based on deep learning and live birth/neonatal outcomes after single vitrified-warmed blastocyst transfer: a single-centre, large-cohort retrospective study.

Authors:  Satoshi Ueno; Jørgen Berntsen; Motoki Ito; Tadashi Okimura; Keiichi Kato
Journal:  J Assist Reprod Genet       Date:  2022-07-26       Impact factor: 3.357

3.  "AI for all" is a matter of social justice.

Authors:  Alessandra Buccella
Journal:  AI Ethics       Date:  2022-09-22

Review 4.  Reporting on the Value of Artificial Intelligence in Predicting the Optimal Embryo for Transfer: A Systematic Review including Data Synthesis.

Authors:  Konstantinos Sfakianoudis; Evangelos Maziotis; Sokratis Grigoriadis; Agni Pantou; Georgia Kokkini; Anna Trypidi; Polina Giannelou; Athanasios Zikopoulos; Irene Angeli; Terpsithea Vaxevanoglou; Konstantinos Pantos; Mara Simopoulou
Journal:  Biomedicines       Date:  2022-03-17

5.  Artificial intelligence-the future is now.

Authors:  Mark P Trolice; Carol Curchoe; Alexander M Quaas
Journal:  J Assist Reprod Genet       Date:  2021-07-07       Impact factor: 3.412

6.  Embryo selection with artificial intelligence: how to evaluate and compare methods?

Authors:  Mikkel Fly Kragh; Henrik Karstoft
Journal:  J Assist Reprod Genet       Date:  2021-06-26       Impact factor: 3.412

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.