Using machine learning approaches and genomic data for fracture risk prediction in the US older men
Main Author: | |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2020-10-01
|
Series: | Bone Reports |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2352187220304605 |
id |
doaj-dc471c082cf84e6cbae9af9801f0bf60 |
---|---|
record_format |
Article |
spelling |
doaj-dc471c082cf84e6cbae9af9801f0bf602020-11-25T03:53:06ZengElsevierBone Reports2352-18722020-10-0113100700Using machine learning approaches and genomic data for fracture risk prediction in the US older menQing Wu0Corresponding author.; University of Nevada, Las Vegas, United Stateshttp://www.sciencedirect.com/science/article/pii/S2352187220304605 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Qing Wu |
spellingShingle |
Qing Wu Using machine learning approaches and genomic data for fracture risk prediction in the US older men Bone Reports |
author_facet |
Qing Wu |
author_sort |
Qing Wu |
title |
Using machine learning approaches and genomic data for fracture risk prediction in the US older men |
title_short |
Using machine learning approaches and genomic data for fracture risk prediction in the US older men |
title_full |
Using machine learning approaches and genomic data for fracture risk prediction in the US older men |
title_fullStr |
Using machine learning approaches and genomic data for fracture risk prediction in the US older men |
title_full_unstemmed |
Using machine learning approaches and genomic data for fracture risk prediction in the US older men |
title_sort |
using machine learning approaches and genomic data for fracture risk prediction in the us older men |
publisher |
Elsevier |
series |
Bone Reports |
issn |
2352-1872 |
publishDate |
2020-10-01 |
url |
http://www.sciencedirect.com/science/article/pii/S2352187220304605 |
work_keys_str_mv |
AT qingwu usingmachinelearningapproachesandgenomicdataforfractureriskpredictionintheusoldermen |
_version_ |
1724479890179227648 |