Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics
Herausgeber: Anavatti, Sreenatha G.; Kumar, Abhishek; Dubey, Ashutosh Kumar
Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics
Herausgeber: Anavatti, Sreenatha G.; Kumar, Abhishek; Dubey, Ashutosh Kumar
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In the last two decades, machine learning has developed dramatically and is still experiencing a fast and everlasting change in paradigms, methodology, applications and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on their diversity and complexity. Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research. It provides many case…mehr
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- Produktdetails
- Verlag: CRC Press
- Seitenzahl: 242
- Erscheinungstermin: 10. März 2022
- Englisch
- Abmessung: 240mm x 161mm x 18mm
- Gewicht: 533g
- ISBN-13: 9780367676339
- ISBN-10: 0367676338
- Artikelnr.: 62606490
- Verlag: CRC Press
- Seitenzahl: 242
- Erscheinungstermin: 10. März 2022
- Englisch
- Abmessung: 240mm x 161mm x 18mm
- Gewicht: 533g
- ISBN-13: 9780367676339
- ISBN-10: 0367676338
- Artikelnr.: 62606490
of Bio Signals. 3. Machine Learning Methods for Managing Parkinson's
Disease. 4. Challenges of Medical Text and Image Processing. 5. Machine
Learning Solutions in Computer-Aided Medical Diagnosis. 6. Rule Learning in
Healthcare and Health Services Research. 7. Diagnosis in Medical Imaging.
8. Identifying Diseases and Diagnosis Using Machine Learning. 9. Machine
Learning-Based Behavioral Modification. 10. Smart Health Records. 11.
Treatment Recommendation System. 12. Smart Health Informatics System. 13.
Natural Language Processing Utilization in Healthcare. 14. Clinical
Decision Support and Predictive Analytics. 15. Bioinformatics and
Biometrics. 16. Human Computer Interfaces and Usability. 17. Education and
Capacity Building. 18. Learning Analytics for Competence Assessment. 19.
Patient Simulators. 20. Serious Gaming. 21. Patient Empowerment and
Engagement. 22. Social Media, Mobile Apps, and Patient Portals. 23. Human
Factors and Technology Adoption. 24. Surveillance System. 25. Robotics. 26.
Object Detection. 27. Traffic Analysis. 28. Big Data in Healthcare Systems.
29. Advanced Decision-Making and Data Analytics. 30. Emergence of Decision
Support Systems. 31. Big Data Based Frameworks and Machine Learning. 32.
Predictive Analysis and Modeling. 33. Security and Privacy with Machine
Learning Systems. 34. Role of Social Media in Healthcare Analytics. 35. Big
Data Based Case Studies for Healthcare Analytics. 36. Machine Learning and
Deep Learning Paradigms and Case Studies. 37. Machine Learning in
Agriculture.
of Bio Signals. 3. Machine Learning Methods for Managing Parkinson's
Disease. 4. Challenges of Medical Text and Image Processing. 5. Machine
Learning Solutions in Computer-Aided Medical Diagnosis. 6. Rule Learning in
Healthcare and Health Services Research. 7. Diagnosis in Medical Imaging.
8. Identifying Diseases and Diagnosis Using Machine Learning. 9. Machine
Learning-Based Behavioral Modification. 10. Smart Health Records. 11.
Treatment Recommendation System. 12. Smart Health Informatics System. 13.
Natural Language Processing Utilization in Healthcare. 14. Clinical
Decision Support and Predictive Analytics. 15. Bioinformatics and
Biometrics. 16. Human Computer Interfaces and Usability. 17. Education and
Capacity Building. 18. Learning Analytics for Competence Assessment. 19.
Patient Simulators. 20. Serious Gaming. 21. Patient Empowerment and
Engagement. 22. Social Media, Mobile Apps, and Patient Portals. 23. Human
Factors and Technology Adoption. 24. Surveillance System. 25. Robotics. 26.
Object Detection. 27. Traffic Analysis. 28. Big Data in Healthcare Systems.
29. Advanced Decision-Making and Data Analytics. 30. Emergence of Decision
Support Systems. 31. Big Data Based Frameworks and Machine Learning. 32.
Predictive Analysis and Modeling. 33. Security and Privacy with Machine
Learning Systems. 34. Role of Social Media in Healthcare Analytics. 35. Big
Data Based Case Studies for Healthcare Analytics. 36. Machine Learning and
Deep Learning Paradigms and Case Studies. 37. Machine Learning in
Agriculture.