Pervasive Patient Timeline for Intensive Care Units

@inproceedings{Braga2016PervasivePT,
  title={Pervasive Patient Timeline for Intensive Care Units},
  author={Andr{\'e} Braga and Filipe Portela and Manuel Filipe Santos and J. Machado and Ant{\'o}nio Abelha and {\'A}lvaro M. Silva and Fernando Rua},
  booktitle={WorldCIST},
  year={2016}
}
This research work explores a new way of presenting and representing information about patients in critical care, which is the use of a timeline to display information. This is accomplished with the development of an interactive Pervasive Patient Timeline able to give to the intensivists an access in real-time to an environment containing patients clinical information from the moment in which the patients are admitted in the Intensive Care Unit (ICU) until their discharge This solution allows… 
Step Towards a Pervasive Data System for Intensive Care Medicine
TLDR
Through the introduction of new functionalities to the current system, it is intended to show the optimization made on the INTCare platform, with the main purpose of increasing its responsiveness.
Towards PWA in Healthcare
Configurable interactive environment for hybrid knowledge- and data-driven geriatric risk assessment
TLDR
An interactive environment allowing the geriatricians and caregivers to access, analyze and precisely annotate or label specific granular cases of interest in a variety of heterogeneous data collected to identify behaviour changes through Smart City IoT and Open Data infrastructure is described.
Towards ambient assisted cities using linked data and data analysis
TLDR
Two of the tools developed during the City4Age project are the individual care monitoring dashboards, which use the stored information to help the caregivers to analyze and interpret the citizens’ behaviour, allowing to detect risks related to MCI and frailty.
Benefits of Bring Your Own Device in Healthcare
TLDR
The organization who embraces BYOD policies found their employees happier, more productive, and more collaborative, and the SWOT analysis of BYOD usage in organization is presented.

References

SHOWING 1-10 OF 32 REFERENCES
Pervasive and Intelligent Decision Support in Intensive Medicine - The Complete Picture
TLDR
This paper is focused in presenting the system architecture and the knowledge obtained by each one of the decision modules: Patient Vital Signs, Critical Events, ICU Medical Scores and Ensemble Data Mining.
A Pervasive Approach to a Real-Time Intelligent Decision Support System in Intensive Medicine
TLDR
A pervasive perspective of the decision making process in the context of INTCare system, an intelligent decision support system for intensive medicine is presented.
Pervasive and Intelligent Decision Support in Critical Health Care Using Ensembles
TLDR
An ensemble strategy was experimented in the context of INTCare system, a pervasive IDSS to automatically predict the organ failure and the outcome of the patients throughout next 24 hours, combining real-time data processing with ensemble approach in the intensive care unit of the Centro Hospitalar do Porto.
Predict hourly patient discharge probability in Intensive Care Units using Data Mining
TLDR
Using the data provided by INTCare system it was possible to induce models with a very good sensitivity (95%) in order to predict the probability of a patient be discharged in the next hour and contribute to improve the decision making process providing new knowledge in real time.
Data Mining Models to Predict Patient's Readmission in Intensive Care Units
TLDR
Recognizing the probability of readmission of patients at ICU will allow for planning discharge more precisely and will allow health professionals to have a better perception on patients’ future conditions in the moment of the hospital discharge.
Real-Time Data Mining Models for Predicting Length of Stay in Intensive Care Units
TLDR
This study presents two data mining approaches to predict LOS in an ICU using admission data and supplementary clinical data of the patient collected in real-time to consider the most recent patient condition when the model is induced.
Pervasive Ensemble Data Mining Models to Predict Organ Failure and Patient Outcome in Intensive Medicine
TLDR
The ensemble approach to improve the decision process in intensive Medicine is explored and the transforming process and model induction are both performed automatically and in real-time.
Real-Time Decision Support Using Data Mining to Predict Blood Pressure Critical Events in Intensive Medicine Patients
TLDR
The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques.
DATA MINING TO PREDICT THE USE OF VASOPRESSORS IN INTENSIVE MEDICINE PATIENTS
TLDR
Data Mining models were induced to predict if a patient will need to take a vasopressor, more specifically: Dopamine, Adrenaline or Noradrenaline, and these models will reduce the need of vasopression drugs by helping intensivists to act and take accurate decision before the vasop compressor be need by the patient.
Real-Time Models to Predict the Use of Vasopressors in Monitored Patients
TLDR
This study focuses on easing some of those difficulties by presenting real-time data mining models capable of predicting if a monitored patient, typically admitted in intensive care, will need to take vasopressors.
...
...