Knowledge Discovery and Data Mining

Krochmal, Magdalena; Husi, Holger

doi:10.1002/9781119183952.ch14

Cited by 4 publications

(1 citation statement)

References 64 publications

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“…Discovered knowledge can be useful in making prominent decisions. Data mining is widely used in fields such as business, medicine, science, engineering and so on [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Prevalence of Diabetes Mellitus in Tiruchirappalli District using Machine Learning

Arockiam¹,

Sathyapriya²,

Jane³

et al. 2019

IJRTE

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Machine learning is a part of AI which develops algorithms to learn patterns and make decision form the massive data. Recently, Machine learning has been used to resolving various critical medical problems. Diabetes is one of the dangerous disease, which can lead to more complicated, including deaths if not timely treated. The study is designed for providing the prevalence of Diabetes Mellitus in Tiruchirappalli district using machine learning algorithms and it was detected that the polluted air causes diabetes disease and also increases the risk of that disease. This proposed work helps the people in preventing diabetes disease using various diabetic attributes with an aim to enhance the quality of healthcare and lessen the diagnoses cost of the disease. In future, the work done may be extended by considering many other attributes and by implementing it through various algorithms to improve the prediction accuracy of diabetes mellitus.

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“…Discovered knowledge can be useful in making prominent decisions. Data mining is widely used in fields such as business, medicine, science, engineering and so on [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Prevalence of Diabetes Mellitus in Tiruchirappalli District using Machine Learning

Arockiam¹,

Sathyapriya²,

Jane³

et al. 2019

IJRTE

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Development of Human Face Literature Database Using Text Mining Approach: Phase I

Kaur

Krishan

Sharma

2018

Journal of Craniofacial Surgery

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The face is an important part of the human body by which an individual communicates in the society. Its importance can be highlighted by the fact that a person deprived of face cannot sustain in the living world. The amount of experiments being performed and the number of research papers being published under the domain of human face have surged in the past few decades. Several scientific disciplines, which are conducting research on human face include: Medical Science, Anthropology, Information Technology (Biometrics, Robotics, and Artificial Intelligence, etc.), Psychology, Forensic Science, Neuroscience, etc. This alarms the need of collecting and managing the data concerning human face so that the public and free access of it can be provided to the scientific community. This can be attained by developing databases and tools on human face using bioinformatics approach. The current research emphasizes on creating a database concerning literature data of human face. The database can be accessed on the basis of specific keywords, journal name, date of publication, author's name, etc. The collected research papers will be stored in the form of a database. Hence, the database will be beneficial to the research community as the comprehensive information dedicated to the human face could be found at one place. The information related to facial morphologic features, facial disorders, facial asymmetry, facial abnormalities, and many other parameters can be extracted from this database. The front end has been developed using Hyper Text Mark-up Language and Cascading Style Sheets. The back end has been developed using hypertext preprocessor (PHP). The JAVA Script has used as scripting language. MySQL (Structured Query Language) is used for database development as it is most widely used Relational Database Management System. XAMPP (X (cross platform), Apache, MySQL, PHP, Perl) open source web application software has been used as the server.The database is still under the developmental phase and discusses the initial steps of its creation. The current paper throws light on the work done till date.

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Accuracy Assessment of Machine Learning Algorithm(s) in Thyroid Dysfunction Diagnosis

Danjuma

Wajiga

Garba

et al. 2022

2022 IEEE Nigeria 4th International Conference on Disruptive Technologies for Sustainable Development (NIGERCON)

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Knowledge Discovery and Data Mining

Cited by 4 publications

References 64 publications

Prevalence of Diabetes Mellitus in Tiruchirappalli District using Machine Learning

Prevalence of Diabetes Mellitus in Tiruchirappalli District using Machine Learning

Development of Human Face Literature Database Using Text Mining Approach: Phase I

Accuracy Assessment of Machine Learning Algorithm(s) in Thyroid Dysfunction Diagnosis

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