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Monitoring Abnormal Patterns with Complex Semantics over ICU Data Streams [chapter]

Xinbiao Zhou, Hongyan Li, Haibin Liu, Meimei Li, Lvan Tang, Yu Fan, Zijing Hu
2006 Lecture Notes in Computer Science  
In this paper we present a new approach MAPS(Monitoring Abnormal Patterns over data Streams) to model and identify the abnormal patterns over the massive data streams.  ...  Compared with other data streams, ICU streaming data have their own features: pseudo-periodicity and polymorphism.  ...  Because in multi-dimensional data streams, each stream has its own repetitious features and semantic meanings.  ... 
doi:10.1007/11821045_20 fatcat:cknebucaxvftlpqjdy6kefn7ee

Online mining abnormal period patterns from multiple medical sensor data streams

Guangyan Huang, Yanchun Zhang, Jie Cao, Michael Steyn, Kersi Taraporewalla
2013 World wide web (Bussum)  
over 1.3 million data points) with a total size of 28 GB data.  ...  But it is a challenge to detect abnormalities from high frequently changed physiological streams data, since abnormalities occur gradually due to the complex situation of patients.  ...  In [20] , a Monitoring Abnormal Patterns over data Streams (MAPS) approach is provided.  ... 
doi:10.1007/s11280-013-0203-y fatcat:gu4ttv6hhbdwlpk4y4fvpzmn4m

DSEC: A Data Stream Engine Based Clinical Information System [chapter]

Yu Fan, Hongyan Li, Zijing Hu, Jianlong Gao, Haibin Liu, Shiwei Tang, Xinbiao Zhou
2006 Lecture Notes in Computer Science  
In DSEC, data stream technology as well as traditional computer mechanism is used to process medical data and improve the quality of service in hospitals.  ...  This demo paper describes a clinical information system: Data Stream Engine based Clinical information system (DSEC).  ...  A number of streaming data called medical data stream are generated by equipments and sensors all over the hospital, especially in the ICU (Intensive Care Unit) with many digital equipments and seriously  ... 
doi:10.1007/11610113_127 fatcat:bg3g2yezcbgu3a7ssczzx7hnhq

A demonstration of the BigDAWG polystore system

A. Elmore, T. Kraska, S. Madden, D. Maier, T. Mattson, S. Papadopoulos, J. Parkhurst, N. Tatbul, M. Vartak, S. Zdonik, J. Duggan, M. Stonebraker (+6 others)
2015 Proceedings of the VLDB Endowment  
This complex application serves the needs of doctors and researchers and provides real-time support for streams of patient data.  ...  To illustrate the promise of this approach, we demonstrate its effectiveness on a hospital application using data from an intensive care unit (ICU).  ...  The interfaces will highlight interactive data browsing, guided exploratory analysis that mines interesting patterns in the data set, real-time monitoring of streaming data, and the ability to run complex  ... 
doi:10.14778/2824032.2824098 fatcat:vzqvocndunbhlgz26tiowj4kki

Modeling Rare Interactions in Time Series Data Through Qualitative Change: Application to Outcome Prediction in Intensive Care Units [article]

Zina Ibrahim, Honghan Wu, Richard Dobson
2020 arXiv   pre-print
in areas such as intensive care medicine, which are characterised by i) continuous monitoring of multivariate variables and non-uniform sampling of data streams, ii) the outcomes are generally governed  ...  We present a model for uncovering interactions with the highest likelihood of generating the outcomes seen from highly-dimensional time series data.  ...  We are interested in areas such as intensive care medicine, which are characterised by i) continuous monitoring of multivariate variables and non-uniform sampling of data streams, ii) the outcomes are  ... 
arXiv:2004.01431v1 fatcat:kx5dpwjogffpxg4rrtmegya4gq

IBM's Health Analytics and Clinical Decision Support

M. S. Kohn, J. Sun, S. Knoop, A. Shabo, B. Carmeli, D. Sow, T. Syed-Mahmood, W. Rapp
2014 IMIA Yearbook of Medical Informatics  
As with all analytic tools, they are limited by the amount and quality of data. Conclusion: Big data is an inevitable part of the future of healthcare.  ...  Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed.  ...  We have shown that computer resources have been or are being developed to use the different kinds of healthcare information, big data, more effectively.  ... 
doi:10.15265/iy-2014-0002 pmid:25123736 pmcid:PMC4287097 fatcat:5gnwywsk7bgnhltc6mim73tuui

Complex Event Processing of Health Data in Real Time Predicting Heart Failure Risk

2019 International journal of recent technology and engineering  
The system monitors the patients of heart failure and predicts heart attacks. When critical conditions are occurs the system warns the patients.  ...  In this article, we develop a scalable system that can perform heart failure prediction techniques based on complex event processing (CEP).  ...  Complex event processing system (CEP) combines precise semantic data with information being processed. The proposed approach combines Semantic Web way and CE model to a health monitoring platform.  ... 
doi:10.35940/ijrte.c6448.098319 fatcat:gkyctmsnpnfldk6vl666q36drq

Mining of Sensor Data in Healthcare: A Survey [chapter]

Daby Sow, Deepak S. Turaga, Michael Schmidt
2012 Managing and Mining Sensor Data  
It starts with a description of healthcare data mining challenges before presenting an overview of applications of data mining in both clinical and non clinical settings.  ...  To reach this goal, it is essential to be able to analyze patient data and turn it into actionable information using data mining.  ...  Furthermore, there are many complex physiological patterns of interest to physicians that cannot be represented by a set of thresholds on sensor data streams.  ... 
doi:10.1007/978-1-4614-6309-2_14 fatcat:abmsziig6vasxag76cid4zdolq

User-centered visual analysis using a hybrid reasoning architecture for intensive care units

Bernard Kamsu-Foguem, Germaine Tchuenté-Foguem, Laurent Allart, Youcef Zennir, Christian Vilhelm, Hossein Mehdaoui, Djamel Zitouni, Hervé Hubert, Mohamed Lemdani, Pierre Ravaux
2012 Decision Support Systems  
To ensure the overview and readability of the increasing volumes of data, some special features are required (e.g., data prioritization, clustering, and selection mechanisms) with the application of analytical  ...  Its potential benefit to the development of user interfaces for intelligent monitors that can assist with the detection and explanation of new, potentially threatening medical events.  ...  streaming time-oriented ICU clinical data, with the sequences of events being learned in the user interface.  ... 
doi:10.1016/j.dss.2012.06.009 fatcat:lm3j7jy3sbathfwbl4dmlqzwui

Thinking in Clinical Nursing Practice: A Study of Critical Care Nurses' Thinking Applying the Think-Aloud, Protocol Analysis Method

Kyung-Ja Han, Hesook Suzie Kim, Mae-Ja Kim, Kyung-Ja Hong, Sungae Park, Soon-Nyoung Yun, Misoon Song, Yoenyi Jung, Haewon Kim, Dong-Oak Debbie Kim, Heejung Choi, Kyungae Kim
2007 Asian Nursing Research  
In addition, three patterns of sequential streaming of thinking (short, intermediate, long) were identified to reveal various ways the nurses dealt with clinical situations involving nursing tasks and  ...  Conclusion This study specifies the initial categories of thoughts for each of the processes and various patterns with which these processes are sequentially combined, providing insights into the ways  ...  Specifying goals: A BP of over 90 is to be maintained in this elderly woman.  ... 
doi:10.1016/s1976-1317(08)60010-9 pmid:25030545 fatcat:bq7mxquhsrc77ijyp3kpgc5b5a

Multi-level temporal abstraction for medical scenario construction

Anne-Sophie Silvent, Michel Dojat, Catherine Garbay
2005 International Journal of Adaptive Control and Signal Processing  
Data abstraction and data mining are based on the management of three key concepts, data, information and knowledge, which are instantiated via an ontology specific of our medical domain application.  ...  The automatic recognition of typical pattern sequences (scenarios), as they are developing, is of crucial importance for computer-aided patient supervision.  ...  In Reference [10] , the authors propose a methodology for extraction of local trends from a stream of ICU data.  ... 
doi:10.1002/acs.855 fatcat:4zh27t2xb5aqxnnwn6nk2vadsa

Decision Support for Tactical Combat Casualty Care Using Machine Learning to Detect Shock

Christopher Nemeth, Adam Amos-Binks, Christie Burris, Natalie Keeney, Yuliya Pinevich, Brian W Pickering, Gregory Rule, Dawn Laufersweiler, Vitaly Herasevich, Mei G Sun
2021 Military medicine  
Introduction The emergence of more complex Prolonged Field Care in austere settings and the need to assist inexperienced providers' ability to treat patients create an urgent need for effective tools to  ...  Machine learning algorithm methods included development of a model trained on publicly available Medical Information Mart for Intensive Care data, then on de-identified data from Mayo Clinic Intensive  ...  Vasopressor use has a semantic meaning related to a patient's data that provides context and appears to capture the strong signal in the patient's ICU stay.  ... 
doi:10.1093/milmed/usaa275 pmid:33499479 fatcat:f2bnrye76nh3pjo7dpkyexiqom

An Introduction to Sensor Data Analytics [chapter]

Charu C. Aggarwal
2012 Managing and Mining Sensor Data  
Query Processing over Semantic States The MIST framework [5] proposes to use Hidden Markov Models (HMMs) for deriving semantic meaning from the sensor values.  ...  Primitive sensor events need to be filtered, aggregated and correlated to generate more semantically rich complex events to facilitate the requirements of up-streaming applications.  ...  Event based processing of sensor data enables tracking and monitoring of physical objects and semantically interpreting complex event patterns.  ... 
doi:10.1007/978-1-4614-6309-2_1 fatcat:pfbx566yfzgqpnjcuzonmxr23q

Autonomic care platform for optimizing query performance

Kristof Steurbaut, Steven Latré, Johan Decruyenaere, Filip De Turck
2013 BMC Medical Informatics and Decision Making  
Background With an increased growth of clinical support services and data sources, clinical information service platforms are becoming more and more complex.  ...  Moreover, in the medical environment the contents of the database is constantly changing with inserts of medical data or updates of existing values from medical devices which monitor the patient at high  ...  In previous work, we applied it to manage multimedia services by extending it with semantic capabilities [19] .  ... 
doi:10.1186/1472-6947-13-120 pmid:24160892 pmcid:PMC3828013 fatcat:2qf53qcqdbc5va3kj5kbxl2mfm

Neurocritical Care: Bench to Bedside (Eds. Claude Hemphill, Michael James) Integrating and Using Big Data in Neurocritical Care

Brandon Foreman
2020 Neurotherapeutics  
The neurocritical care environment increasingly involves EEG, multimodal intracranial monitoring, and complex imaging which preclude comprehensive human synthesis, and requires new concepts to integrate  ...  The critical care environment drives huge volumes of data, and clinicians are tasked with quickly processing this data and responding to it urgently.  ...  Neural networks may be more capable of handling the complexity of data generated in the ICU setting.  ... 
doi:10.1007/s13311-020-00846-1 pmid:32152955 fatcat:rglfdrqm7bawbbs522t2gunvf4
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