Clinical risk factors for fracture among postmenopausal patients at risk for fracture: a historical cohort study using electronic medical record data

2010 ◽  
Vol 29 (2) ◽  
pp. 193-200 ◽  
Author(s):  
Joanne LaFleur ◽  
Carrie McAdam-Marx ◽  
Stephen S. Alder ◽  
Xiaoming Sheng ◽  
Carl V. Asche ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cohort Study ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Clinical Risk Factors ◽  
Medical Record Data ◽  
Historical Cohort ◽  
Electronic Medical Record Data ◽  
Record Data ◽  
Patients At Risk

An Automated Model to Identify Heart Failure Patients at Risk for 30-Day Readmission or Death Using Electronic Medical Record Data

Medical Care ◽  
2010 ◽  
Vol 48 (11) ◽  
pp. 981-988 ◽  
Author(s):  
Ruben Amarasingham ◽  
Billy J. Moore ◽  
Ying P. Tabak ◽  
Mark H. Drazner ◽  
Christopher A. Clark ◽  
...  
Keyword(s):  
Heart Failure ◽  
At Risk ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Medical Record Data ◽  
Heart Failure Patients ◽  
Electronic Medical Record Data ◽  
Record Data ◽  
Patients At Risk

scholarly journals Research on diabetes prediction method based on electronic medical record data analysis

2020 ◽  
Vol 185 ◽  
pp. 03001
Author(s):  
Chen Hui ◽  
Wang Mingyuan ◽  
Tang Dingjun ◽  
Zhang Longwei ◽  
Guo Ziyan ◽  
...  
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Risk Factors ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Network Model ◽  
Neural Network Model ◽  
Medical Record Data ◽  
Electronic Medical Record Data ◽  
Record Data

The continuous progress of computer science and technology has accelerated the pace of informatization construction of the medical system. Medical technology has developed rapidly in various research directions, and the construction of medical IT systems has been continuously improved. The popular application of electronic medical records has produced massive medical data in the medical process. At the same time, in medical behavior, more and more rely on data to make relevant judgments. The coverage of medical equipment is becoming more and more extensive, and the accuracy of data is constantly improving, and the clinical diagnosis is gradually shifting from qualitative judgment to quantitative analysis. Based on the analysis of electronic medical record data, this article studies and analyzes the risk factors leading to diabetes. By analyzing the characteristic variables, the risk factors significantly related to diabetes are obtained as the input variables of the BP neural network model. For complex problems, machine learning algorithms have higher accuracy and stronger generalization capabilities. Based on the BP artificial neural network model, this paper builds and builds a machine learning simulation to predict diabetes.

scholarly journals Use of Electronic Medical Record Data for Quality Improvement in Schizophrenia Treatment

2004 ◽  
Vol 11 (5) ◽  
pp. 351-357 ◽  
Author(s):  
Richard R. Owen ◽  
Carol R. Thrush ◽  
Dale Cannon ◽  
Kevin L. Sloan ◽  
Geoff Curran ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Medical Record Data ◽  
Electronic Medical Record Data ◽  
Record Data

Benchmarking Inpatient Mortality Using Electronic Medical Record Data

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Thomas L. Higgins ◽  
Laura Freeseman-Freeman ◽  
Maureen M. Stark ◽  
Kathy N. Henson
Keyword(s):  
Medical Record ◽  
Electronic Medical Record ◽  
Inpatient Mortality ◽  
Medical Record Data ◽  
Electronic Medical Record Data ◽  
Record Data
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