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Learning Bayesian network parameters from small data sets: application of Noisy-OR gates

Agnieszka Oniśko, Marek J. Druzdzel, Hanna Wasyluk
2001 International Journal of Approximate Reasoning  
We test our method on HEPAR EPAR II II, a model for diagnosis of liver disorders, whose parameters are extracted from a real, small set of patient records.  ...  Diagnostic accuracy of the multiple-disorder model enhanced with the Noisy-OR parameters was 6.7% better than the accuracy of the plain multiple-disorder model and 14.3% better than a single-disorder diagnosis  ...  The HEPAR EPAR II I I model was created and tested using SMILE, an inference engine, and GeNIe, a development environment for reasoning in graphical probabilistic models, both developed at the Decision  ... 
doi:10.1016/s0888-613x(01)00039-1 fatcat:e66ay66eyjhbbjokz57aqx3xiy

Knowledge Integration by Probabilistic Argumentation

Saung Hnin Pwint OO, Nguyen Duy HUNG, Thanaruk THEERAMUNKONG
2020 IEICE transactions on information and systems  
By experiments, effectiveness of this approach on conflict resolution is shown via an example of liver disorder diagnosis. key words: knowledge integration, probabilistic argumentation, probabilistic graphical  ...  models and rules  ...  Peter Lucas, Extraordinary professor of Artificial intelligence, Leiden Institute for Advanced Computer Science, Leiden University for his kindness and providing the HEPAR rule-based sys-  ... 
doi:10.1587/transinf.2019edp7270 fatcat:mnfq663hdzcnpacstqkptsyyg4

The representation of medical reasoning models in resolution-based theorem provers

Peter Lucas
1993 Artificial Intelligence in Medicine  
In particular, attention is paid to the use of a meta-level architecture to improve the applicability of theorem-proving techniques in building expert systems.  ...  In particular, we investigate the logical representation of three typical reasoning models in medicine: diagnostic, anatomical and causal reasoning.  ...  Implementation of the resolution-based theorem prover in COMMON LISP was carried out together with Bob van den Berg, who developed most of the program.  ... 
doi:10.1016/0933-3657(93)90033-y pmid:8004141 fatcat:gnixsv5xejhuhefobp5ndpudfm

A survey on artificial intelligence based techniques for diagnosis of hepatitis variants

Adetokunbo MacGregor John-Otumu, Godswill U. Ogba, Obi C. Nwokonkwo
2020 Journal of Advances in Science and Engineering  
aspect of integrating the major hepatitis variants into a single predictive model using effective intelligent machine learning techniques in order to reduce cost of diagnosis and quick treatment of patients  ...  Results showed that Hepatitis B (30%) and C (3%) were the only types of hepatitis the AI-based techniques were used to diagnose and properly classified out of the five major types, while (67%) of the paper  ...  Conflict of Interests The authors declare that there is no conflict of interests regarding the publication of this paper.  ... 
doi:10.37121/jase.v3i1.83 fatcat:2kb3zwrpunejlcbw26x7xznj6m

Bayesian Network Constraint-Based Structure Learning Algorithms: Parallel and Optimized Implementations in the bnlearn R Package

Marco Scutari
2017 Journal of Statistical Software  
It is well known in the literature that the problem of learning the structure of Bayesian networks is very hard to tackle: Its computational complexity is super-exponential in the number of nodes in the  ...  Efficient implementations of score-based structure learning benefit from past and current research in optimization theory, which can be adapted to the task by using the network score as the objective function  ...  A BN model for the diagnosis of liver disorders from related clinical conditions (e.g., gallstones) and relevant biomarkers (e.g., bilirubin, hepatocellular markers). • ANDES (Conati, Gertner, VanLehn  ... 
doi:10.18637/jss.v077.i02 fatcat:y4ef2b4lcbhj7mg5quu4t4idve

Bayesian Network Constraint-Based Structure Learning Algorithms: Parallel and Optimised Implementations in the bnlearn R Package [article]

Marco Scutari
2015 arXiv   pre-print
It is well known in the literature that the problem of learning the structure of Bayesian networks is very hard to tackle: its computational complexity is super-exponential in the number of nodes in the  ...  Efficient implementations of score-based structure learning benefit from past and current research in optimisation theory, which can be adapted to the task by using the network score as the objective function  ...  A BN model for the diagnosis of liver disorders from related clinical conditions (e.g., gallstones) and relevant biomarkers (e.g., bilirubin, hepatocellular markers). • ANDES (Conati, Gertner, VanLehn  ... 
arXiv:1406.7648v2 fatcat:rwhvlhaosrge7nlndj35ey7gyu

Workload-Aware Materialization of Junction Trees [article]

Martino Ciaperoni, Cigdem Aslay, Aristides Gionis, Michael Mathioudakis
2021 arXiv   pre-print
Bayesian networks are popular probabilistic models that capture the conditional dependencies among a set of variables.  ...  In particular, we seek to leverage information in the workload of probabilistic queries to obtain an optimal workload-aware materialization of junction trees, with the aim to accelerate the processing  ...  All datasets are available online. 3 Child [31] is a model for congenital heart-disease diagnosis in new born "blue babies. " Hepar II [25] is a model for liver-disorder diagnosis.  ... 
arXiv:2110.03475v1 fatcat:frgjfmb5kffopi5phct5crntka

The Disturbance of Hepatic and Serous Lipids in Aristolochic Acid Ι Induced Rats for Hepatotoxicity Using Lipidomics Approach

Junyi Zhou, Yifei Yang, Hongjie Wang, Baolin Bian, Jian Yang, Xiaolu Wei, Yanyan Zhou, Nan Si, Haiyu Zhao
2019 Molecules  
According to the evaluation of pathology slices and serum biochemical indexes, they indicated that the hepatotoxicity induced by AAΙ was reversible to some extent.  ...  The changed lipid markers might serve as characteristics to explain the mechanisms of pathogenesis and progression in hepatotoxicity induced by AAΙ.  ...  Thus, the systemic analysis of the disorder in lipid metabolism was a feasible approach for the diagnosis of AAI liver injury.  ... 
doi:10.3390/molecules24203745 pmid:31627392 pmcid:PMC6832582 fatcat:kw32btdtszbijfjyn3ozyks33i

Sepsis 2017 Paris

2017 Intensive Care Medicine Experimental  
Intensive Care Medicine Experimental 2017, 5(Suppl 1):P1 P2 Extracellular histones induce erythrocyte fragility and anaemia and identification of compounds that prevent this process  ...  Acknowledgement We would like to thank Indian council of Medical research (ICMR) for providing fellowship to Ms. Martin S.  ...  Acknowledgements The authors would like to thank the ICU nursing team and the lab staff for their contribution to this study collecting and processing the samples.  ... 
doi:10.1186/s40635-017-0149-y pmid:28895108 pmcid:PMC5593804 fatcat:ngy6fbeelratzbn7gwp46pepri

An evaluation of computer-aided differential diagnostic models in jaundice

A Malchow-Møller
1994 Danish medical bulletin  
Second evaluation of HEPAR, an expert system for the diagnosis of disorders of the liver and biliary tract. Liver 1991, 1 1, 340-6. Lunderquist A. The radiology of jaundice.  ...  That is, some multiple of 25 x10' computational steps would be required in the present situation.  ... 
pmid:7859518 fatcat:rvxxzotbqvg6tppcqflyyap5fu

Homeopathic Treatments of Upper Respiratory and Otorhinolaryngologic Infections: A Review of Randomized and Observational Studies

Paolo Bellavite, University of Verona
2019 HSOA Journal of Alternative, Complementary & Integrative Medicine  
Due to the heterogeneity of approaches and of drugs used, additional studies will be required to evaluate the possible integration of homeopathy into the standard of care for the treatment of respiratory  ...  In order to take into account the whole mass of literature, the evidence of the clinical effectiveness is summarized according to semi-quantitative criteria, based on the number of randomized and non-randomized  ...  Conflict of Interest The authors declare there is no conflict of interest. The paper was written without funding.  ... 
doi:10.24966/acim-7562/100068 fatcat:7am6dlpzn5f5fl6loq2pst5r4q

Acquired phonological and deep dyslexia

Matthew A. Lambon Ralph, Naida L. Graham
2000 Neurocase  
The implications of this pattern of results in a reader of an orthographically transparent language are discussed with regard to current models of oral reading.  ...  Small AbstractIn the context of a multiple-baseline design, this study demonstrated thc positive effects of behavioural treatment using grapheme to phoneme correspondence rules to treat a female patient  ...  The authors investigated extensively her errors according to serial cognitive neuropsychological models of oral reading.  ... 
doi:10.1080/13554790008402767 fatcat:nkf4tpqghrd2nidpnvireuxcei

Acquired Phonological and Deep Dyslexia

M. A. Lambon Ralph
2000 Neurocase  
The implications of this pattern of results in a reader of an orthographically transparent language are discussed with regard to current models of oral reading.  ...  Small AbstractIn the context of a multiple-baseline design, this study demonstrated thc positive effects of behavioural treatment using grapheme to phoneme correspondence rules to treat a female patient  ...  The authors investigated extensively her errors according to serial cognitive neuropsychological models of oral reading.  ... 
doi:10.1093/neucas/6.2.141 fatcat:uctosxgkrnegznifrp3kuz3szu

USCAP 2018 Abstracts: Liver (1719–1811)

2018 Modern Pathology  
Modern Pathology 2018; 31 (suppl 2): page# USCAP ABSTRACTS GEARED LEARN TO 107TH ANNUAL MEETING  ...  as a surrogate model to study regression of fibrosis.  ...  to stain multiple antigens on the same cell or cellular compartment.  ... 
doi:10.1038/modpathol.2018.17 pmid:29551794 fatcat:mdg3ygcxpnd73psjnrsrgsrv74

USCAP 2018 Abstracts: Liver (1719–1811)

2018 Laboratory Investigation  
as a surrogate model to study regression of fibrosis.  ...  to stain multiple antigens on the same cell or cellular compartment.  ...  AGXT may aid in the diagnostic workup for hepatocellular carcinoma expecially in conjunction with ARG1 to increase the sensitivity.  ... 
doi:10.1038/labinvest.2018.17 pmid:29551815 fatcat:ds6voaqtb5bjvl5uei5wy53tfm
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