A machine learning-based framework to identify type 2 diabetes through electronic health records.
about
The derivation and validation of a simple model for predicting in-hospital mortality of acutely admitted patients to internal medicine wards.Cognitive impairment in cerebellar lesions: a logit model based on neuropsychological testingGatekeeping and the utilization of community health services in Shenzhen, China: A cross-sectional study.Electronic Health Record Driven Prediction for Gestational Diabetes Mellitus in Early Pregnancy.Predicting Length of Stay for Obstetric Patients via Electronic Medical Records.Learning Bundled Care Opportunities from Electronic Medical Records.Predicting and explaining inflammation in Crohn's disease patients using predictive analytics methods and electronic medical record data.Causal risk factor discovery for severe acute kidney injury using electronic health records.Opportunities and obstacles for deep learning in biology and medicine.Identifying people at risk of developing type 2 diabetes: A comparison of predictive analytics techniques and predictor variables
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A machine learning-based framework to identify type 2 diabetes through electronic health records.
description
2016 nî lūn-bûn
@nan
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
2016年论文
@zh
2016年论文
@zh-cn
name
A machine learning-based frame ...... ugh electronic health records.
@en
A machine learning-based frame ...... ugh electronic health records.
@nl
type
label
A machine learning-based frame ...... ugh electronic health records.
@en
A machine learning-based frame ...... ugh electronic health records.
@nl
prefLabel
A machine learning-based frame ...... ugh electronic health records.
@en
A machine learning-based frame ...... ugh electronic health records.
@nl
P2093
P2860
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P1476
A machine learning-based frame ...... ough electronic health records
@en
P2093
Mingrong You
Xiaoying He
P2860
P304
P356
10.1016/J.IJMEDINF.2016.09.014
P50
P577
2016-10-01T00:00:00Z