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eXiT*CBR: A framework for case-based medical diagnosis development and experimentation
2011
Artificial Intelligence in Medicine
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The eXiT*CBR framework is proposed to support the development of and experimentation with new case-based reasoning (CBR) systems for medical diagnosis. ...
Method : Our framework offers a modular, heterogeneous environment that combines different CBR techniques for different application requirements. ...
In this work a specific CBR tool for medical applications is presented to support CBR system development, experiment replication and result inter-pretation. ...
doi:10.1016/j.artmed.2010.09.002
pmid:20971621
fatcat:dwdshqtufrelhpxxwv6ovnbwq4
Chronic Kidney Disease Diagnosis Model Based on Case Based Reasoning
2019
International Journal of Engineering and Advanced Technology
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Hence, in this paper we proposed a framework for CBR system to facilitate and support the diagnosis of chronic kidney diseases with domain expert's advice. ...
Provision of health care services is still a major challenge for developing countries. ...
The component of core packages is the final and important step for creating a new application where the CBR application is configured.
a. ...
doi:10.35940/ijeat.b3624.129219
fatcat:kww57oc5nbb7figwdt7co2tuja
Mémoire: Case Based Reasoning Meets the Semantic Web in Biology and Medicine
[chapter]
2004
Lecture Notes in Computer Science
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Mémoire is a framework for the sharing and distribution of case bases and case based reasoning in biology and medicine. ...
The approach could be extended to other application domains of CBR. ...
It will also provide the basis for developing a CBR shell for rapid development of CBR systems in biology and medicine. ...
doi:10.1007/978-3-540-28631-8_5
fatcat:tcxcqkudhnfrhc2raq6tstqlfa
Impact of Genetic Optimization on the Prediction Performance of Case-Based Reasoning Algorithm in Liver Disease
2017
International Journal of Performability Engineering
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We proposed a GA-based CBR framework to compare its performance with CBR in order to observe how effective it is at predicting liver illness. ...
CBR methodology has been implemented to find the prediction results of liver disease for different datasets. ...
Integrated GA and CBR model To develop an integrated framework of GA and CBR model there are some steps need to perform as demonstrated in Figure 1 . ...
doi:10.23940/ijpe.17.04.p2.348361
fatcat:h7s2jk3ffffmvfenmpx3u2uaxa
Knowledge management system in falling risk for physiotherapy care of elderly
2014
Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific
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The diagnosis information derived from the process of KMS helps support the physiotherapist to determine serious falling risks in the elderly and recommend guidelines for medical treatment. ...
in the form of tool and application at the right time. ...
ACKNOWLEDGMENT This study has been conducted with the College of Art Media and Technology at Chiang Mai University, Thailand in collaboration with the Faculty of Associated Medical Sciences, Chiang Mai ...
doi:10.1109/apsipa.2014.7041812
dblp:conf/apsipa/RueangsirarakCM14
fatcat:qlggu42qcnfb5cg7cngrmn5aiy
Framework Architecture for Improving Healthcare Information Systems using Agent Technology
2015
International Journal of Managing Information Technology
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Preliminary experimental simulation based on Agent Development Framework (JADE) demonstrated the feasibility of this model. ...
CBR is used to generate advices to a certain e-healthcare problems by analyzing solutions given to previously solved problems and to build intelligent systems for disease diagnostics and prognosis. ...
Agents use a platform for developing agent applications and to operate so as to achieve their objectives. ...
doi:10.5121/ijmit.2015.7102
fatcat:uj5tkeuthbhiffweex35xsa45q
Constructing Ontology-Based Cancer Treatment Decision Support System with Case-Based Reasoning
[article]
2018
arXiv
pre-print
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Decision support is a probabilistic and quantitative method designed for modeling problems in situations with ambiguity. ...
The proposed DSS uses Case-Based Reasoning (CBR) to consider disease manifestations and provides physicians with treatment solutions from similar previous cases for reference. ...
Medical Reasoning Framework Based on our previous work [3] , Fig. 2 presents the relations between diagnosis (Δ), prognosis (Π), and treatment (Θ) and describes a series of medical inference rules using ...
arXiv:1812.01891v1
fatcat:ybhqgcjgnbfozeedwhlirk4geq
A case-based reasoning framework for early detection and diagnosis of novel coronavirus
2020
Informatics in Medicine Unlocked
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The CBR model leverages on a novel feature selection and the semantic-based mathematical model proposed in this study for case similarity computation. ...
It is, therefore, crucial to expedite the process of early detection and diagnosis of the disease across the world. ...
This will allow for future studies using ontologies and CBR paradigm to select or even combine similarity metrics effectively. ...
doi:10.1016/j.imu.2020.100395
pmid:32835080
pmcid:PMC7377815
fatcat:ev22hazq7vbtfaplcvvouq2dci
DERMA: A Melanoma Diagnosis Platform Based on Collaborative Multilabel Analog Reasoning
2014
The Scientific World Journal
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Experiments using subsystems specialized in confocal and dermoscopy images have provided promising results for helping experts to assess melanoma diagnosis. ...
The system has to face up several challenges that include data characterization, pattern matching, reliable diagnosis, and self-explanation capabilities. ...
Acknowledgment The authors thank the Agencia de Gestio d' Ajuts Universitaris i de Recerca for funding the Grup de Recerca en Sistemes Intel⋅ligents as recognized group (2009-SGR-183) and for Grant 2010FI ...
doi:10.1155/2014/351518
pmid:24578629
pmcid:PMC3918694
fatcat:lnh5hvcogze5lbqtloa6ug6zp4
Case-Based Reasoning in the Health Sciences: Foundations and Research Directions
[chapter]
2010
Studies in Computational Intelligence
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Case-based reasoning (CBR) is an Artificial Intelligence (AI) approach with broad applicability to building intelligent systems in health sciences domains. ...
It begins with introductions to the CBR approach and to health sciences domains, and then explains their synergistic combination. ...
application of a generic CBR framework. ...
doi:10.1007/978-3-642-14464-6_7
fatcat:iaxh4h4ty5fcbjmo3ovn3xtvhe
Diabetes Diagnosis by Case-Based Reasoning and Fuzzy Logic
2018
International Journal of Interactive Multimedia and Artificial Intelligence
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Sharma and Mehrotra [49] used the jColibri framework to develop a CBR application for diagnosis of chronic kidney disease while Kiragu and Waiganjo [50] developed a prototype for treatment and management ...
Houeland [22] developed a RDT (random decision tree) algorithm implemented in a CBR framework. RDT algorithm has been combined with a simple similarity measure. ...
doi:10.9781/ijimai.2018.02.001
fatcat:leiqk2ep6jhynlsgxwus2kwrdi
Case-Based Reasoning for Biomedical Informatics and Medicine
[chapter]
2014
Springer Handbook of Bio-/Neuroinformatics
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Diagnosis with CBR Systems Other CBR frameworks that have been used in the medical domain are jCOLIBRI [13.72] and MyCBR [13.73]. ...
Medical Imaging and CBR Systems All the aforementioned systems handle textual and numerical data in medical diagnosis applications. ...
doi:10.1007/978-3-642-30574-0_13
fatcat:mqwi7hwuzngvfccrgpc7w7u2hi
Case-based reasoning for assessment and diagnosis of depression in palliative care
2010
2010 IEEE 23rd International Symposium on Computer-Based Medical Systems (CBMS)
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The goal of the research presented is to create a computational framework and system architecture for clinical decision support in palliative care. ...
The method under investigation is case-based reasoning, motivated by the complexity of the domain and a lack of generalized principles of sufficient coverage and strength for diagnosis and treatment. ...
Acknowledgements The European Palliative Care Research Collaborative is funded by the European Commission"s Sixth Framework Programme (contract no LSHC-CT-2006-037777, EPCRC) with the overall aim to improve ...
doi:10.1109/cbms.2010.6042692
dblp:conf/cbms/AamodtGLWS10
fatcat:2vxfoq4p7fcu7et7yb5ejjn6mi
Preface
2004
Applied intelligence (Boston)
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Research integrating CBR with a soft computing framework for developing efficient methodologies and algorithms for various decision making applications has drawn the attention of scientists. ...
for performing different tasks of CBR with real life applications. ...
Dillon, Shiu and Pal A model to forecast parameters of a complex and dynamic environment in an unsupervised way is developed in the next article by Fdez-Riverola and Corchado. ...
doi:10.1023/b:apin.0000043623.41336.bf
fatcat:qdl3bjsls5f4bdtykj4l5gkz5a
Usage of Case-Based Reasoning, Neural Network and Adaptive Neuro-Fuzzy Inference System Classification Techniques in Breast Cancer Dataset Classification Diagnosis
2010
Journal of medical systems
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Many theoretical and experimental studies have shown that a multiple classifier system is an effective technique for reducing prediction errors. ...
This study compared the particle swarm optimizer (PSO) based artificial neural network (ANN), the adaptive neuro-fuzzy inference system (ANFIS), and a case-based reasoning (CBR) classifier with a logistic ...
In medical applications, CBR and machine learning have been successfully used for decision support in tasks such as patient diagnosis [3] . ...
doi:10.1007/s10916-010-9485-0
pmid:20703710
fatcat:gsh3egegerewvhpm3fw4ity2ji
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