Presentation

Bioinformatics and Medical Applications

0 purchase

Course
Bioinformatics and Medical Applications

Institution
Bioinformatics And Medical Applications

"The main topics addressed in this book are big data analytics problems in bioinformatics research such as microarray data analysis, sequence analysis, genomics-based analytics, disease network analysis, techniques for big data analytics, and health information technology. Bioinformatics and Medic...

[Show more]

Preview 4 out of 216 pages

View example

Uploaded on August 7, 2024
Number of pages 216
Written in 2020/2021
Type Presentation
Person Unknown

bioinformatics and medical applications

$4.99

Add to cart

Add to wishlist

100% satisfaction guarantee
Immediately available after payment
Both online and in PDF
No strings attached

,Table of Contents
1. Cover
2. Title Page
3. Copyright
4. Preface
5. 1 Probabilistic Optimization of Machine Learning Algorithms for Heart Disease Prediction
1. 1.1 Introduction
2. 1.2 Literature Review
3. 1.3 Tools and Techniques
4. 1.4 Proposed Method
5. 1.5 Conclusion
6. References
6. 2 Cancerous Cells Detection in Lung Organs of Human Body: IoT-Based Healthcare 4.0
Approach
1. 2.1 Introduction
2. 2.2 Literature Review
3. 2.3 Proposed Systems
4. 2.4 Experimental Results and Analysis
5. 2.5 Novelties
6. 2.6 Future Scope, Limitations, and Possible Applications
7. 2.7 Recommendations and Consideration
8. 2.8 Conclusions
9. References
7. 3 Computational Predictors of the Predominant Protein Function: SARS-CoV-2 Case
1. 3.1 Introduction
2. 3.2 Human Coronavirus Types
3. 3.3 The SARS-CoV-2 Pandemic Impact
4. 3.4 Computational Predictors
5. 3.6 Future Implications
6. 3.7 Acknowledgments
7. References
8. 4 Deep Learning in Gait Abnormality Detection: Principles and Illustrations
1. 4.1 Introduction
2. 4.2 Background
3. 4.3 Related Works
4. 4.4 Methods
5. 4.5 Conclusion and Future Work
6. 4.6 Acknowledgments
7. References
9. 5 Broad Applications of Network Embeddings in Computational Biology, Genomics,
Medicine, and Health
1. 5.1 Introduction
2. 5.2 Types of Biological Networks
3. 5.3 Methodologies in Network Embedding
4. 5.4 Attributed and Non-Attributed Network Embedding

, 5. 5.5 Applications of Network Embedding in Computational Biology
6. 5.6 Limitations of Network Embedding in Biology
7. 5.7 Conclusion and Outlook
8. References
10. 6 Heart Disease Classification Using Regional Wall Thickness by Ensemble Classifier
1. 6.1 Introduction
2. 6.2 Related Study
3. 6.3 Methodology
4. 6.4 Implementation and Result Analysis
5. 6.5 Conclusion
6. References
11. 7 Deep Learning for Medical Informatics and Public Health
1. 7.1 Introduction
2. 7.2 Deep Learning Techniques in Medical Informatics and Public Health
3. 7.3 Applications of Deep Learning in Medical Informatics and Public Health
4. 7.4 Open Issues Concerning DL in Medical Informatics and Public Health
5. 7.5 Conclusion
6. References
12. 8 An Insight Into Human Pose Estimation and Its Applications
1. 8.1 Foundations of Human Pose Estimation
2. 8.2 Challenges to Human Pose Estimation
3. 8.3 Analyzing the Dimensions
4. 8.4 Standard Datasets for Human Pose Estimation
5. 8.5 Deep Learning Revolutionizing Pose Estimation
6. 8.6 Application of Human Pose Estimation in Medical Domains
7. 8.7 Conclusion
8. References
13. 9 Brain Tumor Analysis Using Deep Learning: Sensor and IoT-Based Approach for
Futuristic Healthcare
1. 9.1 Introduction
2. 9.2 Literature Survey
3. 9.3 System Design and Methodology
4. 9.4 Novelty in Our Work
5. 9.5 Future Scope, Possible Applications, and Limitations
6. 9.6 Recommendations and Consideration
7. 9.7 Conclusions
8. References
14. 10 Study of Emission From Medicinal Woods to Curb Threats of Pollution and Diseases:
Global Healthcare Paradigm Shift in 21st Century
1. 10.1 Introduction
2. 10.2 Literature Survey
3. 10.3 The Methodology and Protocols Followed
4. 10.4 Experimental Setup of an Experiment
5. 10.5 Results and Discussions
15. 11 An Economical Machine Learning Approach for Anomaly Detection in IoT
Environment

, 1. 11.1 Introduction
2. 11.2 Literature Survey
3. 11.3 Proposed Work
4. 11.4 Analysis of the Work
5. 11.5 Conclusion
6. References
16. 12 Indian Science of Yajna and Mantra to Cure Different Diseases: An Analysis Amidst
Pandemic With a Simulated Approach
1. 12.1 Introduction
2. 12.2 Literature Survey
3. 12.3 Methodology
4. 12.4 Results and Discussion
5. 12.5 Interpretations and Analysis
6. 12.6 Novelty in Our Work
7. 12.7 Recommendations
8. 12.8 Future Scope and Possible Applications
9. 12.9 Limitations
10. 12.10 Conclusions
11. 12.11 Acknowledgments
12. References
17. 13 Collection and Analysis of Big Data From Emerging Technologies in Healthcare
1. 13.1 Introduction
2. 13.2 Data Collection
3. 13.3 Data Analysis
4. 13.4 Research Trends
5. 13.5 Conclusion
6. References
18. 14 A Complete Overview of Sign Language Recognition and Translation Systems
1. 14.1 Introduction
2. 14.2 Sign Language Recognition
3. 14.3 Dataset Creation
4. 14.4 Hardware Employed for Sign Language Recognition
5. 14.5 Computer Vision–Based Sign Language Recognition and Translation Systems
6. 14.6 Sign Language Translation System—A Brief Overview
7. 14.7 Conclusion
8. References
19. Index
20. End User License Agreement

List of Illustrations
1. Chapter 1
1. Figure 1.1 Heatmap of input attributes.
2. Figure 1.2 Age distribution.
3. Figure 1.3 Presence of cardiovascular disease.
4. Figure 1.4 Cholesterol type distribution.

The benefits of buying summaries with Stuvia:

Guaranteed quality through customer reviews

Stuvia customers have reviewed more than 700,000 summaries. This how you know that you are buying the best documents.

Quick and easy check-out

You can quickly pay through credit card or Stuvia-credit for the summaries. There is no membership needed.

Focus on what matters

Your fellow students write the study notes themselves, which is why the documents are always reliable and up-to-date. This ensures you quickly get to the core!

Frequently asked questions

What do I get when I buy this document?

You get a PDF, available immediately after your purchase. The purchased document is accessible anytime, anywhere and indefinitely through your profile.

Satisfaction guarantee: how does it work?

Our satisfaction guarantee ensures that you always find a study document that suits you well. You fill out a form, and our customer service team takes care of the rest.

Who am I buying these notes from?

Stuvia is a marketplace, so you are not buying this document from us, but from seller RobertCuong. Stuvia facilitates payment to the seller.

Will I be stuck with a subscription?

No, you only buy these notes for $4.99. You're not tied to anything after your purchase.

Can Stuvia be trusted?

4.6 stars on Google & Trustpilot (+1000 reviews)

68175 documents were sold in the last 30 days

Founded in 2010, the go-to place to buy study notes for 15 years now

Start selling