Literature DB >> 19201398

Knowledge and intelligent computing system in medicine.

Babita Pandey1, R B Mishra.   

Abstract

Knowledge-based systems (KBS) and intelligent computing systems have been used in the medical planning, diagnosis and treatment. The KBS consists of rule-based reasoning (RBR), case-based reasoning (CBR) and model-based reasoning (MBR) whereas intelligent computing method (ICM) encompasses genetic algorithm (GA), artificial neural network (ANN), fuzzy logic (FL) and others. The combination of methods in KBS such as CBR-RBR, CBR-MBR and RBR-CBR-MBR and the combination of methods in ICM is ANN-GA, fuzzy-ANN, fuzzy-GA and fuzzy-ANN-GA. The combination of methods from KBS to ICM is RBR-ANN, CBR-ANN, RBR-CBR-ANN, fuzzy-RBR, fuzzy-CBR and fuzzy-CBR-ANN. In this paper, we have made a study of different singular and combined methods (185 in number) applicable to medical domain from mid 1970s to 2008. The study is presented in tabular form, showing the methods and its salient features, processes and application areas in medical domain (diagnosis, treatment and planning). It is observed that most of the methods are used in medical diagnosis very few are used for planning and moderate number in treatment. The study and its presentation in this context would be helpful for novice researchers in the area of medical expert system.

Mesh:

Year:  2009        PMID: 19201398     DOI: 10.1016/j.compbiomed.2008.12.008

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  12 in total

1.  Multiscale Time-Sharing Elastography Algorithms and Transfer Learning of Clinicopathological Features of Uterine Cervical Cancer for Medical Intelligent Computing System.

Authors:  Xiaojun Dong; Hongmei Du; Haichen Guan; Xuezhen Zhang
Journal:  J Med Syst       Date:  2019-08-26       Impact factor: 4.460

2.  Usage of case-based reasoning, neural network and adaptive neuro-fuzzy inference system classification techniques in breast cancer dataset classification diagnosis.

Authors:  Mei-Ling Huang; Yung-Hsiang Hung; Wen-Ming Lee; R K Li; Tzu-Hao Wang
Journal:  J Med Syst       Date:  2010-05-02       Impact factor: 4.460

3.  Fuzzy logic: A "simple" solution for complexities in neurosciences?

Authors:  Saniya Siraj Godil; Muhammad Shahzad Shamim; Syed Ather Enam; Uvais Qidwai
Journal:  Surg Neurol Int       Date:  2011-02-26

4.  Comparison of adaptive neuro-fuzzy inference system and artificial neutral networks model to categorize patients in the emergency department.

Authors:  Dhifaf Azeez; Mohd Alauddin Mohd Ali; Kok Beng Gan; Ismail Saiboon
Journal:  Springerplus       Date:  2013-08-29

Review 5.  Computer-based diagnostic expert systems in rheumatology: where do we stand in 2014?

Authors:  Hannes Alder; Beat A Michel; Christian Marx; Giorgio Tamborrini; Thomas Langenegger; Pius Bruehlmann; Johann Steurer; Lukas M Wildi
Journal:  Int J Rheumatol       Date:  2014-07-08

6.  Decision Support System for Lymphoma Classification.

Authors:  Ahmed E-S Negm; Ahmed H Kandil; Osama A E-F Hassan
Journal:  Curr Med Imaging Rev       Date:  2017-02

7.  The Prediction of the Risk Level of Pulmonary Embolism and Deep Vein Thrombosis through Artificial Neural Network.

Authors:  Laleh Agharezaei; Zhila Agharezaei; Ali Nemati; Kambiz Bahaadinbeigy; Farshid Keynia; Mohammad Reza Baneshi; Abedin Iranpour; Moslem Agharezaei
Journal:  Acta Inform Med       Date:  2016-11-01

8.  A systematic review of the applications of Expert Systems (ES) and machine learning (ML) in clinical urology.

Authors:  Hesham Salem; Daniele Soria; Jonathan N Lund; Amir Awwad
Journal:  BMC Med Inform Decis Mak       Date:  2021-07-22       Impact factor: 2.796

9.  γ -H2AX: A Novel Prognostic Marker in a Prognosis Prediction Model of Patients with Early Operable Non-Small Cell Lung Cancer.

Authors:  E Chatzimichail; D Matthaios; D Bouros; P Karakitsos; K Romanidis; S Kakolyris; G Papashinopoulos; A Rigas
Journal:  Int J Genomics       Date:  2014-01-08       Impact factor: 2.326

10.  Brain activity and medical diagnosis: an EEG study.

Authors:  Laila Massad Ribas; Fábio Theoto Rocha; Neli Regina Siqueira Ortega; Armando Freitas da Rocha; Eduardo Massad
Journal:  BMC Neurosci       Date:  2013-10-01       Impact factor: 3.288

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