Mining electronic health records (EHRs) A survey
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 …
attention. Central to the ideas aimed at curbing this trend is the use of technology in the form …
[HTML][HTML] Predicting patient deterioration: a review of tools in the digital hospital setting
Background Early warning tools identify patients at risk of deterioration in hospitals.
Electronic medical records in hospitals offer real-time data and the opportunity to automate …
Electronic medical records in hospitals offer real-time data and the opportunity to automate …
Predicting hospital readmission via cost-sensitive deep learning
With increased use of electronic medical records (EMRs), data mining on medical data has
great potential to improve the quality of hospital treatment and increase the survival rate of …
great potential to improve the quality of hospital treatment and increase the survival rate of …
Big data in psychology: A framework for research advancement.
The potential for big data to provide value for psychology is significant. However, the pursuit
of big data remains an uncertain and risky undertaking for the average psychological …
of big data remains an uncertain and risky undertaking for the average psychological …
An intelligent warning model for early prediction of cardiac arrest in sepsis patients
Background Sepsis-associated cardiac arrest is a common issue with the low survival rate.
Early prediction of cardiac arrest can provide the time required for intervening and …
Early prediction of cardiac arrest can provide the time required for intervening and …
[HTML][HTML] Artificial intelligence in predicting cardiac arrest: scoping review
Background: Cardiac arrest is a life-threatening cessation of activity in the heart. Early
prediction of cardiac arrest is important, as it allows for the necessary measures to be taken …
prediction of cardiac arrest is important, as it allows for the necessary measures to be taken …
A ranking-based cross-entropy loss for early classification of time series
Early classification tasks aim to classify time series before observing full data. It is critical in
time-sensitive applications such as early sepsis diagnosis in the intensive care unit (ICU) …
time-sensitive applications such as early sepsis diagnosis in the intensive care unit (ICU) …
Data-driven automatic treatment regimen development and recommendation
The analysis of large-scale Electrical Medical Records (EMRs) has the potential to develop
and optimize clinical treatment regimens. A treatment regimen usually includes a series of …
and optimize clinical treatment regimens. A treatment regimen usually includes a series of …
Blood pressure prediction via recurrent models with contextual layer
Recently, the percentage of people with hypertension is increasing, and this phenomenon is
widely concerned. At the same time, wireless home Blood Pressure (BP) monitors become …
widely concerned. At the same time, wireless home Blood Pressure (BP) monitors become …
[HTML][HTML] Toward analyzing and synthesizing previous research in early prediction of cardiac arrest using machine learning based on a multi-layered integrative …
Background One of the significant problems in the field of healthcare is the low survival rate
of people who have experienced sudden cardiac arrest. Early prediction of cardiac arrest …
of people who have experienced sudden cardiac arrest. Early prediction of cardiac arrest …