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A Review on Different Kinds of Artificial Intelligence Solutions in TCM Syndrome Differentiation Application

Yujuan Song, Bin Zhao, Jun Jia, Xuebing Wang, Sibai Xu, Zhenjing Li, Xu Fang, Wen Si
2021 Evidence-Based Complementary and Alternative Medicine  
However, an endless stream of artificial intelligence methods was applied in the field of Chinese medicine research, expert system, artificial neural network, data mining, and multivariate analysis; not  ...  It also provides a theoretical background for the upcoming fully automated research on TCM syndrome differentiation and diagnosis robot.  ...  Bayesian learning help to acquire object-oriented knowledge [25, 26] . e decision tree is a tree structure which solves the problem of syndrome differentiation and classification in TCM.  ... 
doi:10.1155/2021/6654545 pmid:33763146 pmcid:PMC7963904 fatcat:xksoigl5ivf2vjmjngc22c3pnm

Guaranteeing Correctness of Machine Learning based Decision Making at Higher Educational Institutions

Muhammad Nauman, Nadeem Akhtar, Adi Alhudhaif, Abdulrahman Alothaim
2021 IEEE Access  
The authors would also like to thank Directorate of Information Technology, The Islamia University Bahawalpur for providing admission data for academic research purposes.  ...  ACKNOWLEDGMENT This publication was supported by the Deanship of Scientific Research at Prince Sattam bin Abdulaziz University, Alkharj, Saudi Arabia.  ...  Formal verification is the process of establishing the correctness, safety, and liveness properties of complex software and hardware systems.  ... 
doi:10.1109/access.2021.3088901 fatcat:rpviiipfuja2vdzcpyepqerw4y

Improving the Correctness of Medical Diagnostics Based on Machine Learning With Coloured Petri Nets

Muhammad Nauman, Nadeem Akhtar, Omar H. Alhazmi, Mustafa Hameed, Habib Ullah, Nadia Khan
2021 IEEE Access  
Use of formalism makes it possible to ensure that prognostic decisions are correct and understandable. Empirical results show that we have increased the accuracy of prognostic decisions by up to 90%.  ...  INDEX TERMS Medical diagnosis, breast cancer prognosis, decision making, supervised machine learning, decision trees, formal verification, formal methods, coloured petri nets.  ...  The generalisation error of a tree classifier forest depends on the strength of each tree in the forest and the correlation between them.  ... 
doi:10.1109/access.2021.3121092 fatcat:v7kljpjsvrg5ze52cd2e5yjzuq

An Adaptive Modeling and Execution Framework for a Knowledge-Based Intelligent Clinical Decision Support System to Predict Schizophrenia
IJARCCE - Computer and Communication Engineering

Adekunle Y.A
2015 IJARCCE  
In the framework the patient information is fed into the system; the Knowledge base of the system stores all the information to be used by the Clinical Decision Support System and the classification algorithm  ...  selected after an exhaustive evaluation of relevant classification algorithms for this work is the C5.0 Decision Tree Algorithm with its percentage of correctly classified instances given as 78.4534%;  ...  SVMs can learn a larger set of patterns and be able to scale better, because the classification complexity does not depend on the dimensionality of the feature space.  ... 
doi:10.17148/ijarcce.2015.42101 fatcat:3oqk4mpwhzhrngtyw63wm3vadm

A Comparative Study on Different Types of Approaches to Text Categorization

Pratiksha Y. Pawar, S. H. Gawande
2012 International Journal of Machine Learning and Computing  
Text Categorization is a pattern classification task for text mining and necessary for efficient management of textual information systems.  ...  This paper presents a comparative study on different types of approaches to text categorization.  ...  Rule based approaches mean ones where classification rules are defined manually and documents are classified based on rules.  ... 
doi:10.7763/ijmlc.2012.v2.158 fatcat:aum7nxk3kba75h4liw53u554bu

Page 5642 of Mathematical Reviews Vol. , Issue 2004g [page]

2004 Mathematical Reviews  
[Moshkov, Mikhail] (RS-NZNVCC; Nizhnii Novgorod) Classification of infinite information systems depending on complexity of decision trees and decision rule systems. (English summary) Fund.  ...  Time and space complexity of decision trees and complete decision rule systems are studied. For the web version of Mathematical Reviews, see http: //  ... 

A constrained method of constructing the logic classification trees on the basis of elementary attribute selection

Igor Povkhan
2020 International Workshop on Computer Modeling and Intelligent Systems  
A problem of constructing the logic classification tree model on the basis of a constrained elementary attribute selection method for the geologic data array has been considered.  ...  The method of the real data array approximation by a set of elementary attributes with a fixed criterion of the branching procedure stopping at the stage of constructing the classification tree has been  ...  even for a qualified expert to form a set of recommendations; iii) synthesis of rules (classification rules, decision rules) in the natural language; iv) the resulting tree-like model obtained is intuitively  ... 
dblp:conf/cmis/Povkhan20 fatcat:eahxfpjyejhdfbyksl7rdnx244

An Analysis of Software Bug Reports Using Machine Learning Techniques

Ha Manh Tran, Son Thanh Le, Sinh Van Nguyen, Phong Thanh Ho
2019 SN Computer Science  
This approach aims at constructing multiple decision trees based on the subsets of the existing bug dataset and features, and then selecting the best decision trees to assess the severity and priority  ...  Determining these features is challenging and depends heavily on human being, e.g., software developers or system operators, especially for assessing a large number of error and warning events occurring  ...  Time consumption for random forest also depends on constructing multiple decision trees and selecting the best decision trees. Processing large bug datasets consumes much time.  ... 
doi:10.1007/s42979-019-0004-1 fatcat:su2ywdgclvavhbwia3tbptir7a

A Classification Framework based on VPRS Boundary Region using Random Forest Classifier

Hemant Kumar, Sanjay Keer
2017 International Journal of Computer Applications  
Decision tree algorithm is the most common classifier to build tree because of it is easier to implement and understand.  ...  efficient and scalable approach for classification of various datasets.  ...  VPRSBRRF Classifier Now, propose our algorithm to generate a decision tree in the following way: Input: An information system Output: A decision tree T.  ... 
doi:10.5120/ijca2017912842 fatcat:l34lqrvsxbhupjp77c2sjzxopm

A Survey on the Explainability of Supervised Machine Learning [article]

Nadia Burkart, Marco F. Huber
2020 arXiv   pre-print
Insights about the decision making are mostly opaque for humans. Particularly understanding the decision making in highly sensitive areas such as healthcare or fifinance, is of paramount importance.  ...  The decision-making behind the black boxes requires it to be more transparent, accountable, and understandable for humans.  ...  This approach focuses on the information about how a system generates output, on its dependencies and on the possible information that could transport trust.  ... 
arXiv:2011.07876v1 fatcat:ccquewit2jam3livk77l5ojnqq

Evaluating triggers using decision trees

Lance Obermeyer, Daniel P. Miranker
1997 Proceedings of the sixth international conference on Information and knowledge management - CIKM '97  
Regions of the state space represent particular combinations of enabled rules. Decision trees are then generated based on the subdivided state space.  ...  The algorithm generates one or more decision trees that determine what rules or triggers might be enabled by an individual database element, reducing the number of rules or triggers that must be evaluated  ...  Tree Generation Given a list of chssifications, the next task is to generate a binary decision tree such that any leaf of the tree corresponds to one and only classification.  ... 
doi:10.1145/266714.266885 dblp:conf/cikm/ObermeyerM97 fatcat:htkkbfy7ozhqdmffv7q6nsoqpm

A Survey on Medical Text Mining

Revathi MNair, Sindhu L.
2014 International Journal of Computer Applications  
Medical diagnosis is considered as an important yet complicated task that needs to be executed accurately and efficiently. The automation of this system will be very useful for the medical field.  ...  Due to recent technology advances, large masses of medical data are available. These large data contain valuable information for diagnosing diseases.  ...  of decision tree. ii).  ... 
doi:10.5120/18985-0423 fatcat:ojefyjsh5jgmplefdeonzhewtm

Designing a Rule Based Expert Systems for Contact Lenses Patients

İbrahim Berkan Aydilek, Abdülkadir Gümüşçü
2018 International Journal of Information Technology and Computer Science  
Rules are created by human experts on the way and added upon the system.  ...  Learning problems are valid with expert systems. Therefore, they cannot add new rules and information automatically by themselves.  ...  Classification data sets, depending on the information inside, contain various knowledge in the related domain.  ... 
doi:10.5815/ijitcs.2018.03.03 fatcat:qptrz52wirf6xiiimvyjjkjz6e

1.2 Financial applications

2014 2014 International Conference on Field-Programmable Technology (FPT)  
On its basis function π * it (F i,t−1 ) ∈ S is estimated in the class of binary decision rules represented by classification trees.  ...  Hence as a result investor gets a decision rule in class "long/short/neutral" dependent on historical technical and fundamental data of DAX30 companies.  ... 
doi:10.1109/fpt.2014.7082751 fatcat:phhnpf2pvfc5xibwkbfpamcxs4

A Survey on the Explainability of Supervised Machine Learning

Nadia Burkart, Marco F. Huber
2021 The Journal of Artificial Intelligence Research  
Insights about the decision making are mostly opaque for humans. Particularly understanding the decision making in highly sensitive areas such as healthcare or finance, is of paramount importance.  ...  The decision-making behind the black boxes requires it to be more transparent, accountable, and understandable for humans.  ...  Acknowledgments This work is partially supported by the Ministry of Economic Affairs of the state Baden-Württemberg within the KI-Fortschrittszentrum "Lernende Systeme", Grant No. 036-170017.  ... 
doi:10.1613/jair.1.12228 fatcat:nd3hfatjknhexb5eabklk657ey
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