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Handbook of research on disease pred...
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Rani, Geeta, (1980-)
Handbook of research on disease prediction through data analytics and machine learning
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Handbook of research on disease prediction through data analytics and machine learningGeeta Rani and Pradeep Kumar Tiwari, editors.
其他作者:
Rani, Geeta,
出版者:
Hershey, Pennsylvania :IGI Global,2020.
面頁冊數:
1 online resource (xxx, 586 p.)
標題:
Machine learning.
電子資源:
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-2742-9
ISBN:
9781799827436 (ebk.)
Handbook of research on disease prediction through data analytics and machine learning
Handbook of research on disease prediction through data analytics and machine learning
[electronic resource] /Geeta Rani and Pradeep Kumar Tiwari, editors. - Hershey, Pennsylvania :IGI Global,2020. - 1 online resource (xxx, 586 p.)
Includes bibliographical references and index.
Chapter 1. Glaucoma detection using convolutional neural networks -- Chapter 2. Pre-processing highly sparse and frequently evolving standardized electronic health records for mining -- Chapter 3. Image classification techniques -- Chapter 4. Prediction models -- Chapter 5. Prediction models for healthcare using machine learning: a review -- Chapter 6. Chronic kidney disease prediction using data mining algorithms -- Chapter 7. A machine learning approach to prevent cancer -- Chapter 8. Machine learning perspective in cancer research -- Chapter 9. A pathway to differential modelling of Nipah virus -- Chapter 10. Application of AI for computer-aided diagnosis system to detect brain tumors -- Chapter 11. Application of machine learning to analyse biomedical signals for medical diagnosis -- Chapter 12. Artificial bee colony-based associative classifier for healthcare data diagnosis -- Chapter 13. Artificial intelligence approaches to detect neurodegenerative disease from medical records: a perspective -- Chapter 14. Clinical decision support systems: decision-making system for clinical data -- Chapter 15. Diagnosis and prognosis of ultrasound fetal growth analysis using neuro-fuzzy based on genetic algorithms -- Chapter 16. ECG image classification using deep learning approach -- Chapter 17. Genetic data analysis -- Chapter 18. Heart disease prediction using machine learning -- Chapter 19. Heuristic approach performances for artificial neural networks training -- Chapter 20. Mental health through biofeedback is important to analyze: an app and analysis -- Chapter 21. Pre-clustering techniques for healthcare system: evaluation measures, evaluation metrics, comparative study of existing vs. proposed approaches -- Chapter 22. Strategic analysis in prediction of liver disease using different classification algorithms -- Chapter 23. Texture segmentation and features of medical images -- Chapter 24. Towards integrating data mining with knowledge-based system for diagnosis of human eye diseases: the case of an African hospital -- Chapter 25. Use of IoT and different biofeedback to measure TTH: an approach for healthcare 4.0 -- Chapter 26. ACO_NB-based hybrid prediction model for medical disease diagnosis.
ISBN: 9781799827436 (ebk.)Subjects--Topical Terms:
188639
Machine learning.
LC Class. No.: R853.S7 / H36 2020
Dewey Class. No.: 616.0072/7
Handbook of research on disease prediction through data analytics and machine learning
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Chapter 1. Glaucoma detection using convolutional neural networks -- Chapter 2. Pre-processing highly sparse and frequently evolving standardized electronic health records for mining -- Chapter 3. Image classification techniques -- Chapter 4. Prediction models -- Chapter 5. Prediction models for healthcare using machine learning: a review -- Chapter 6. Chronic kidney disease prediction using data mining algorithms -- Chapter 7. A machine learning approach to prevent cancer -- Chapter 8. Machine learning perspective in cancer research -- Chapter 9. A pathway to differential modelling of Nipah virus -- Chapter 10. Application of AI for computer-aided diagnosis system to detect brain tumors -- Chapter 11. Application of machine learning to analyse biomedical signals for medical diagnosis -- Chapter 12. Artificial bee colony-based associative classifier for healthcare data diagnosis -- Chapter 13. Artificial intelligence approaches to detect neurodegenerative disease from medical records: a perspective -- Chapter 14. Clinical decision support systems: decision-making system for clinical data -- Chapter 15. Diagnosis and prognosis of ultrasound fetal growth analysis using neuro-fuzzy based on genetic algorithms -- Chapter 16. ECG image classification using deep learning approach -- Chapter 17. Genetic data analysis -- Chapter 18. Heart disease prediction using machine learning -- Chapter 19. Heuristic approach performances for artificial neural networks training -- Chapter 20. Mental health through biofeedback is important to analyze: an app and analysis -- Chapter 21. Pre-clustering techniques for healthcare system: evaluation measures, evaluation metrics, comparative study of existing vs. proposed approaches -- Chapter 22. Strategic analysis in prediction of liver disease using different classification algorithms -- Chapter 23. Texture segmentation and features of medical images -- Chapter 24. Towards integrating data mining with knowledge-based system for diagnosis of human eye diseases: the case of an African hospital -- Chapter 25. Use of IoT and different biofeedback to measure TTH: an approach for healthcare 4.0 -- Chapter 26. ACO_NB-based hybrid prediction model for medical disease diagnosis.
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-2742-9
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