A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Filters
A Medical Informatics Perspective on Decision Support
2009
IMIA Yearbook of Medical Informatics
Preserved Fulltext
to process large patient sets; 2. narrow clinical applications focused on in-depth real-time signal processing for a specific population or medical specialty. ...
Altogether these papers support the idea that more elaborated computer tools, likely to combine together textual and highly structured data, including real-time data contents, are needed. ...
I also would like to thank Casimir Kulikowski and Antoine Geissbuhler for the inspired discussions we had during the selection process. ...
doi:10.1055/s-0038-1638645
fatcat:evnpaip6gjderkurxs6bw56oza
A Decision Support System For Predicting Hospitalization Of Hemodialysis Patients
2009
Zenodo
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
In this study we combined temporal abstraction with data mining techniques for analyzing the dialysis patients' biochemical data to develop a decision support system. ...
The mined temporal patterns are helpful for clinicians to predict hospitalization of hemodialysis patients and to suggest them some treatments immediately to avoid hospitalization. ...
ACKNOWLEDGMENT We are grateful to the National Science Council for the grants program (NSC 96-2221-E-415-005), and to the Hemodialysis Center of Chiayi Yang Ming Hospital for their professional consultations ...
doi:10.5281/zenodo.1331128
fatcat:b7cdiau5wrehplmqz7v7bo6vr4
Application of K-Means Technique in Data Mining to Cluster Hemodialysis Patients
2017
International Robotics & Automation Journal
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
The results obtained from the data mining model in this research can be useful for the decision makers and doctors. ...
In the next stage, the data was processed and prepared to be used as the input data for the implementation of data mining techniques. ...
The goal of this research is to use data mining techniques to help create such a decision support tool for medical doctors dealing with ESRD patients in future. ...
doi:10.15406/iratj.2017.02.00013
fatcat:fapgeuihxbgbfk7u5njoy767ua
Predicting the Appearance of Hypotension during Hemodialysis Sessions Using Machine Learning Classifiers
2021
International Journal of Environmental Research and Public Health
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
However, the analytical information is not always available to the healthcare personnel, or it is far in time, so the clinical parameters monitored during the session become key to the prevention of hypotension ...
The prediction model takes into account up to 22 clinical parameters measured five times during the session, as well as the gender and age of the patient. ...
Its technology is particularly suited for analyzing medical data and making decisions in medical diagnostic problems [26] . ...
doi:10.3390/ijerph18052364
pmid:33671029
fatcat:3qc7pf4hkjdulaxxdhjrqvrfzy
Data mining in predicting survival of kidney dialysis patients
2003
Lasers in Surgery: Advanced Characterization, Therapeutics, and Systems XIII
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2010; you can also visit the original URL.
The file type is application/pdf.
Two different data mining algorithms are employed for extracting knowledge in the form of decision rules. ...
In this research, a data mining approach is used to elicit knowledge about the interaction between these variables and patient survival. ...
ACKNOWLEDGEMENT Our special thanks to Katherine Ruth Coates, Sara Ann Dolny, Katherine Gaunt, and Katie Louise Kruse for preparation different versions of data sets. ...
doi:10.1117/12.476387
fatcat:k262lwh36rbxxnudq5tmjnggom
Development, implementation and user experience of the Veterans Health Administration (VHA) dialysis dashboard
2020
BMC Nephrology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Data on user experience and perceptions were collected via an e-mail questionnaire to dialysis medical directors and nurse managers at these facilities. ...
Respondents indicated that they used the dialysis dashboard for clinical reporting (71%), quality assessment/performance improvement (QAPI) (62%), and decision-making (23%). ...
While clinical dashboards provide timely clinical data to clinicians so that they can make informed daily decisions about patient care, quality dashboards display information on performance measures at ...
doi:10.1186/s12882-020-01798-6
pmid:32299383
fatcat:5ex6lv2kqrad7ox3hivsukefpy
Guest Editorial Special Section on New and Emerging Technologies in Bioinformatics and Bioengineering
2010
IEEE Transactions on Information Technology in Biomedicine
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2015; you can also visit the original URL.
The file type is application/pdf.
Computational Intelligence and Data Mining in Support of Decision Making in Biomedicine Machine learning and data mining facilitates biomedical data exploration using data analysis methods with sophisticated ...
9] - [11] to imaging [12] , [13] and decision making [7] , [14] in the life sciences domain. ...
doi:10.1109/titb.2010.2048660
pmid:20684050
fatcat:gwerjlnpxzh7nnlmadzvzjigue
Integrating Real Time Data to Improve Outcomes in Acute Kidney Injury
2015
Nephron
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
This connection facilitates automated data capture of many variables -including delivered dose, ultrafiltration rate and pressure measurements -which in turn can be leveraged for data mining, quality improvement ...
One major barrier to effective care of these patients is the traditional dissociation of dialysis device data from other clinical information systems, notably the electronic health record (EHR). ...
coordination with other clinical variables and precludes improving clinical outcomes using automated data driven clinical decision-making [26] . ...
doi:10.1159/000441981
pmid:26575177
fatcat:ruxbgow25faj3atfib4tnxw5ci
Artificial Intelligence for the Artificial Kidney: Pointers to the Future of a Personalized Hemodialysis Therapy
2018
Kidney Diseases
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Furthermore, great efforts are dedicated to develop miniaturized artificial kidneys to achieve a continuous and personalized dialysis therapy, in order to improve the patient's quality of life. ...
These innovative dialysis devices will require a real-time monitoring of equipment alarms, dialysis parameters, and patient-related data to ensure patient safety and to allow instantaneous changes of the ...
to decision making. ...
doi:10.1159/000486394
pmid:29594137
pmcid:PMC5848485
fatcat:x24qgxt2bnh7xnzwafc4o2vnvy
An architecture of Multiagent System (MAS) for healthcare Intelligent Decision Support System (IDSS)
2018
Journal of Fundamental and Applied Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Currently, the healthcare domain is very complex with a growing of medical knowledge, a growing size of medical data, a dynamic data and process, a distributed environment and a concurring decision making ...
Consequently, in [8] suggested a healthcare decision making process framework to clarify those healthcare decision making processes. ...
Currently, DSS development also showed a wide use of data mining technique. This is because the efficacy of using the data mining approach or known as intelligent technique in the DSS development. ...
doi:10.4314/jfas.v9i5s.12
fatcat:2uqh2ygmlbak3ipcpkwjhnc5pa
Using Artificial Intelligence Resources in Dialysis and Kidney Transplant Patients: A Literature Review
2020
BioMed Research International
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
We identified 43 trials in the first group, 8 in the second, and 18 in the third. Then, studies were classified according to the type of algorithm. Results. ...
We searched four electronic databases or studies that used AI/ML in hemodialysis (HD), peritoneal dialysis (PD), and kidney transplantation (KT). ...
Supplemental Table 2 : short description and results of the studies involving AI in PD. ...
doi:10.1155/2020/9867872
pmid:32596403
pmcid:PMC7303737
fatcat:xtqwjydqnzaezicg56zrwekl4q
Information Systems and Healthcare XXXIV: Clinical Knowledge Management Systems—Literature Review and Research Issues for Information Systems
2010
Communications of the Association for Information Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
In this paper, we focus on clinical knowledge management systems (CKMS) research. ...
The objectives of the paper are to evaluate the current state of knowledge management systems diffusion in the clinical setting, assess the present status and focus of CKMS research efforts, and identify ...
One system was noted to facilitate knowledge sharing with respect to ethical decision-making in the clinical setting [Frize et al., 2005] . ...
doi:10.17705/1cais.02626
fatcat:gv5a4f3byrczff6ffc3ptk3mzi
Predictive data mining in clinical medicine: a focus on selected methods and applications
2011
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Predictive data mining in clinical medicine deals with learning models to predict patients' health. The models can be devoted to support clinicians in diagnostic, therapeutic, or monitoring tasks. ...
Data mining methods are usually applied in clinical contexts to analyze retrospective data, thus giving healthcare professionals the opportunity to exploit large amounts of data routinely collected during ...
In a clinical scenario, such patterns can be conveniently used as a decisional support tool to predict future healthcare events. ...
doi:10.1002/widm.23
fatcat:n6juaunarbcclkfur3ojwb6zpq
A comparison between physicians and computer algorithms for form CMS-2728 data reporting
2016
Hemodialysis International
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
We used all available procedure, billing, laboratory, and prescription data to generate predictive models of physician annotations. ...
We aimed to examine the predictability of provider annotations for 8 clinical conditions. ...
Finally, the use of machine learning techniques can be a valuable tool in understanding annotations patterns in order to guide development of decision support systems.
Disclosures ...
doi:10.1111/hdi.12445
pmid:27353890
fatcat:qcl2o6y7qndvrewbdlleq4ku6i
Neuro-Fuzzy Technology as a Predictor of Parathyroid Hormone Level in Hemodialysis Patients
2007
Tohoku journal of experimental medicine
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Neuro-fuzzy technology is increasingly used for data analysis and decision-making purposes in clinical medicine (Hanai and Honda 2004; Ramesh et al. 2004 ). ...
Our reason is that for any forecasting model to be useful in making clinical decisions, it should use only parameters that are readily available to the clinician at the time of triage (Chiu et al. 2005 ...
doi:10.1620/tjem.211.81
pmid:17202775
fatcat:yd4asb5kzzcrxk5ezcgy7dysui
« Previous
Showing results 1 — 15 out of 749 results