Towards Integrating Data Mining With Knowledge-Based System for Diagnosis of Human Eye Diseases

2021 ◽  
pp. 470-485
Author(s):  
Nilamadhab Mishra ◽  
Johny Melese Samuel
Keyword(s):  
Data Mining ◽  
Vision Loss ◽  
Eye Diseases ◽  
Eye Disease ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Extraction Algorithm ◽  
Hidden Knowledge ◽  
Vision Function

The eye is the most important sensory organ of vision function. But some eye diseases can lead to vision loss, so it is important to identify and treat eye disease as early as possible. Eye care professionals can help protect their patients from vision loss or blindness by recognizing common eye diseases and recommending for an eye exam. Eye diseases with early detection, treatment, and appropriate follow-up care, vision loss, and blindness from eye disease can be prevented or delayed. In this study, rule-based eye disease identification and advising the knowledge-based system are projected. The projected system is targeting using hidden knowledge extracted by employing the extraction algorithm of data mining. To identify the best prediction model for the diagnosis of eye disease, four experiments for four classification algorithms were performed. Finally, the researchers decided to use the rules of the J48 pruned classification algorithm for further use in the development of a knowledge base of KBS because it exhibited better performance with a 98.5% evaluation result.

scholarly journals Burden of vision loss associated with eye disease in China 1990–2020: findings from the Global Burden of Disease Study 2015

2017 ◽  
Vol 102 (2) ◽  
pp. 220-224 ◽  
Author(s):  
Bingsong Wang ◽  
Nathan Congdon ◽  
Rupert Bourne ◽  
Yichong Li ◽  
Kai Cao ◽  
...  
Keyword(s):  
Vision Loss ◽  
Eye Diseases ◽  
Eye Disease ◽  
Global Burden ◽  
International Forum ◽  
Health Loss ◽  
Global Burden Of Diseases ◽  
Disease Study ◽  
Years Lived With Disability ◽  
Burden Of Diseases

AimsTo assess the burden of vision loss due to eye disease in China between 1990 and 2015, and to predict the burden in 2020.MethodsData from the GBD 2015 (Global Burden of Diseases, Injuries, and Risk Factors Study 2015) were used. The main outcome measures were prevalence and years lived with disability (YLDs) for vision loss due to cataract, glaucoma, macular degeneration, other vision loss, refraction and accommodation disorders and trachoma.ResultsPrevalence for eye diseases increased steadily from 1990 to 2015, and will increase until 2020. From 1990 to 2015, the most common eye disorder was refraction and accommodation disorders. From 1990 to 2015, the vision loss burden due to eye disease decreased for those aged 0–14 years, and increased for those aged 15 years and above, with the most notable increases occurring among those aged 50 years and above. China ranked 10th when comparing YLDs for vision loss due to eye disease with the other members of the G20 (Group of Twenty, an international forum for the governments from 20 major economies) . Age-standardised YLD rates for vision loss due to eye disease declined in all 19 countries, except for China. The burden from vision loss due to eye disease ranked 12th and 11th among all causes of health loss in China in 1990 and 2015, respectively.ConclusionAlone among major economies, China has experienced an increase in the burden of age-standardised vision loss from eye disease over the last two decades. In the future, China may expect a growing burden of vision loss due to population growth and ageing.

scholarly journals Developing a Prototype Knowledge-Based System for Diagnosis and Treatment of Diabetes Using Data Mining Techniques

2020 ◽  
Vol 30 (1) ◽  
Author(s):  
Kedir Eyasu ◽  
Worku Jimma ◽  
Takele Tadesse
Keyword(s):  
Data Mining ◽  
Expert Knowledge ◽  
Diagnosis And Treatment ◽  
Data Mining Techniques ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
The Status ◽  
Treatment Of Diabetes ◽  
Using Data ◽  
Accuracy Of Results

BACKGROUND: Diabetes is a disease that affects the body’s ability to produce or use insulin. A total of 425 million people are suffering from diabetes in the world. Of this, more than 16 million people live in the Africa Region, which is estimated to be around 41 million by 2045. The main objective of this study was to design and develop a prototype knowledge-based system using data mining techniques for diagnosis and treatment of diabetes.METHODS: For this study, experimental research design was employed, and the researchers used domain expert knowledge as a supplement of data mining techniques whereby three classification algorithms in WEKA; namely J48, PART and JRip were used, and finally the researchers decided to use the results of J48 classification algorithm. Ultimate Visual basic studio 2013 (Vb.net) was used to store knowledge and as front side of prototype. Common lisp prolog (Clisp) was used for obtained knowledge back end coding.RESULTS: Using a decision tree algorithm; namely J48, 2512 (95.1515%) of the instances were classified correctly, and 128 (4.8485 %) were classified incorrectly. The second most performing model was generated by JRip Classier. This model scored the 94.7348% accuracy on the general data to classify the status of diabetic patient datasets. It classified the 2501 instances of the records correctly.CONCLUSION: The J48 model was the best performing model with the best accuracy of results. 

Assessment of Knowledge and Practice of Various Eye Diseases in Sulaimani: A Descriptive Study

2018 ◽  
pp. 1-6
Author(s):  
Abdulrahman M. Ibrahem ◽  
Salah Q. Mahmood ◽  
Muhammed Babakir-Mina ◽  
Salar Ibrahim Ali ◽  
Bakhtyar Kamal Talabany
Keyword(s):  
Vision Loss ◽  
Good Practice ◽  
Study Data ◽  
Eye Diseases ◽  
Vision Impairment ◽  
P Value ◽  
Published Data ◽  
Knowledge Level ◽  
Cross Sectional ◽  
Knowledge And Practice

Knowledge and practice of public, especially patients about eye diseases are important to reduce magnitude of human blindness. Vision and sight are very essential because they allow us to connect to each other’s. In accordance to the recently published data; the estimation of 253 million people lives with vision impairment, 36 million are blind and 217 million suffer from moderate to severe vision impairment. A descriptive cross-sectional study was conducted at Shahid Dr. Aso Hospital in Sulaimani city-Iraq, from April to August 2017 by face-to-face interview through close ended questionnaire for data collecting. All data were analyzed by Statistical Package for Social Sciences version 22.0 software. P-value of < 0.05 was considered as a statistically significant. A total of 430 patients were randomly chosen to participate in the study. They were 254 (59.1%) males and 176 (40.9%) females. 76.7% of respondents was worrying about vision loss, 0.7% was worrying about hair loss. Of the participants, 32.8% was with a good knowledge level and 40.5% was with a poor knowledge level, as well as 3.1% was in a good practice and 58.8% was in a poor practice level. Female knowledge mean score was 9.53±4.96 and male knowledge mean score was 8.42±5.45, the practice mean score of males was 4.33±1.96 and mean practice score of females was 4.13±1.93. The study data indicate the worrying of participates about vision loss is in the highest proportion and the awareness and practice of patients about eye diseases is unsatisfactory. Health education campaigns are needed to improve personal awareness about vision related problems and for better eye health.

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