World Library  


Add to Book Shelf
Flag as Inappropriate
Email this Book

Plos One : Prediction of Age at Menopause from Assessment of Ovarian Reserve May Be Improved by Using Body Mass Index and Smoking Status, Volume 8

By Borras, Consuelo

Click here to view

Book Id: WPLBN0003965027
Format Type: PDF eBook :
File Size:
Reproduction Date: 2015

Title: Plos One : Prediction of Age at Menopause from Assessment of Ovarian Reserve May Be Improved by Using Body Mass Index and Smoking Status, Volume 8  
Author: Borras, Consuelo
Volume: Volume 8
Language: English
Subject: Journals, Science, Medical Science
Collections: Periodicals: Journal and Magazine Collection (Contemporary)
Historic
Publication Date:
Publisher: Plos

Citation

APA MLA Chicago

Borras, C. (n.d.). Plos One : Prediction of Age at Menopause from Assessment of Ovarian Reserve May Be Improved by Using Body Mass Index and Smoking Status, Volume 8. Retrieved from http://worldebookfair.com/


Description
Description : In the present study we confirmed the good level of conformity between the distributions of observed and AMH-predicted ages at menopause, and showed that using BMI and smoking status as additional variables improves AMHbased prediction of age at menopause.

 

Click To View

Additional Books


  • Plos One : Identification and Analysis o... (by )
  • Plos One : Nf-kb-dependent Role for Cold... (by )
  • Plos One : Aerobic Capacity, Activity Le... (by )
  • Plos One : Predictive Computational Mode... (by )
  • Plos One : Filament-filament Switching C... (by )
  • Plos One : Peer Support and Exclusive Br... (by )
  • Plos One : Molecular Characterization of... (by )
  • Plos One : Autotaxin-lysophosphatidic Ac... (by )
  • Plos One : Predictive Value of the Tuber... (by )
  • Plos One : Tnap and Ehd1 Are Over-expres... (by )
  • Plos One : Selaginella Tamariscina Atten... (by )
  • Plos One : Functional Selection of Shrna... (by )
Scroll Left
Scroll Right

 



Copyright © World Library Foundation. All rights reserved. eBooks from World eBook Fair are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.