Mining electronic health records (EHRs) A survey

P Yadav, M Steinbach, V Kumar, G Simon - ACM Computing Surveys …, 2018 - dl.acm.org
The continuously increasing cost of the US healthcare system has received significant
attention. Central to the ideas aimed at curbing this trend is the use of technology in the form …

Factors influencing the development of primary care data collection projects from electronic health records: a systematic review of the literature

ML Gentil, M Cuggia, L Fiquet, C Hagenbourger… - BMC medical informatics …, 2017 - Springer
Background Primary care data gathered from Electronic Health Records are of the utmost
interest considering the essential role of general practitioners (GPs) as coordinators of …

[HTML][HTML] Dealing with missing, imbalanced, and sparse features during the development of a prediction model for sudden death using emergency medicine data …

X Chen, H Chen, S Nan, X Kong… - JMIR Medical …, 2023 - medinform.jmir.org
Background In emergency departments (EDs), early diagnosis and timely rescue, which are
supported by prediction modes using ED data, can increase patients' chances of survival …

[HTML][HTML] Improving the quality and design of retrospective clinical outcome studies that utilize electronic health records

O Dziadkowiec, J Durbin, VJ Muralidharan… - … Healthcare Journal of …, 2020 - ncbi.nlm.nih.gov
Background Electronic health records (EHRs) have primarily been developed to allow for
more efficient and complete medical billing. Secondary “core functions” of EHRs, as defined …

[HTML][HTML] Clustering clinical models from local electronic health records based on semantic similarity

KR Gøeg, R Cornet, SK Andersen - Journal of biomedical informatics, 2015 - Elsevier
Background Clinical models in electronic health records are typically expressed as
templates which support the multiple clinical workflows in which the system is used. The …

[HTML][HTML] Clustering datasets with demographics and diagnosis codes

H Zhong, G Loukides, R Gwadera - Journal of biomedical informatics, 2020 - Elsevier
Clustering data derived from Electronic Health Record (EHR) systems is important to
discover relationships between the clinical profiles of patients and as a preprocessing step …

[PDF][PDF] An Efficient and Scalable Technique for Clustering Comorbidity Patterns of Diabetic Patients from Clinical Datasets

SM Bramesh, AK KM - … Journal of Modern Education and Computer …, 2022 - mecs-press.org
Clustering diabetic patients with comorbidity patterns are necessary to learn relationships
between diabetes patients' clinical profiles and as an essential pre-processing stage for …

Exploratory analysis of electronic health records using topic modeling

D Duarte, I Puerari, G Dal Bianco… - Journal of Information …, 2020 - periodicos.ufmg.br
The rapid growth of electronic health record (EHR) systems brings the increase of available
information about patients in hospitals. This massive amount of text information represents …

[HTML][HTML] Analysis of Factors Affecting the Adoption of Health Technologies: Modification of the UTAUT2 model

G Malekzadeh, M Trojanowski - Payesh (Health Monitor), 2021 - payeshjournal.ir
Objective (s): In a threatening situation such as Covid-19 Pandemic, E-health is more
effective in providing public health, including prevention, monitoring, diagnosis …

[图书][B] Statistical Methods for Learning Patients Heterogeneity and Treatment Effects to Achieve Precision Medicine

T Xu - 2022 - search.proquest.com
The burgeoning adoption of modern technologies provides a great opportunity for gathering
multiple modalities of comprehensive personalized data on individuals. The thesis aims to …