Cardiac Data Mining for Heart Disease Prediction from Biomedical Warehouses
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9789062712595
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"Cardiac Data Mining for Heart Disease Prediction from Biomedical Warehouses" by Mujtaba Ashraf Qureshi is a comprehensive study on the use of data mining techniques to predict heart disease using biomedical warehouses. Qureshi discusses the importance of data mining in healthcare and the potential benefits it can provide in the field of cardiac health.
Through an extensive review of literature and experimentation, Qureshi explores the most effective data mining algorithms for heart disease prediction and examines the role of various risk factors. The author also discusses the challenges and limitations of cardiac data mining and offers potential solutions to overcome these obstacles.
Whether you are a healthcare professional, researcher, or data scientist interested in the latest advancements in heart disease prediction, "Cardiac Data Mining for Heart Disease Prediction from Biomedical Warehouses" is an essential resource. Order your copy today and discover how data mining can help improve cardiac health outcomes.
Publisher: Independent Author
Published: 04/04/2023
Pages: 166
Weight: 0.51lbs
Size: 9.00h x 6.00w x 0.35d
ISBN: 9789062712595
Through an extensive review of literature and experimentation, Qureshi explores the most effective data mining algorithms for heart disease prediction and examines the role of various risk factors. The author also discusses the challenges and limitations of cardiac data mining and offers potential solutions to overcome these obstacles.
Whether you are a healthcare professional, researcher, or data scientist interested in the latest advancements in heart disease prediction, "Cardiac Data Mining for Heart Disease Prediction from Biomedical Warehouses" is an essential resource. Order your copy today and discover how data mining can help improve cardiac health outcomes.
Publisher: Independent Author
Published: 04/04/2023
Pages: 166
Weight: 0.51lbs
Size: 9.00h x 6.00w x 0.35d
ISBN: 9789062712595