Clustering polycystic ovary syndrome laboratory results extracted from a large internet forum with machine learning-Reference-Cited by-同舟云学术

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Clustering polycystic ovary syndrome laboratory results extracted from a large internet forum with machine learning

Published:2024 Issue: Volume:9 Page:100135
ISSN:2666-5212
Container-title:Intelligence-Based Medicine
language:en
Short-container-title:Intelligence-Based Medicine

Author:

Emanuel Rebecca H.K.^ORCID,Docherty Paul D.^ORCID,Lunt Helen^ORCID,Murray Rua^ORCID,Campbell Rebecca E.

Funder

University of Canterbury

Publisher

Elsevier BV

Reference44 articles.

1. Phenotypes and body mass in women with polycystic ovary syndrome identified in referral versus unselected populations: systematic review and meta-analysis;Lizneva;Fertil Steril,2016

2. Phenotypic spectrum of polycystic ovary syndrome: clinical and biochemical characterization of the three major clinical subgroups;Chang;Fertil Steril,2005

3. Heterogeneity of the polycystic ovary syndrome: clinical, endocrine and ultrasound features in 556 patients;Conway;Clin Endocrinol,1989

4. Women with polycystic ovary syndrome have intrinsic insulin resistance on euglycaemic–hyperinsulaemic clamp;Stepto;Hum Reprod,2013

5. Insulin resistance in a large cohort of women with polycystic ovary syndrome: a comparison between euglycaemic-hyperinsulinaemic clamp and surrogate indexes;Tosi;Hum Reprod,2017

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