DBDMLDLHA 2020: Demystifying Big Data, Machine Learning and Deep Learning for Healthcare Analytics |
Submission link | https://easychair.org/conferences/?conf=dbdmldlha2020 |
Poster | download |
Abstract registration deadline | December 15, 2019 |
Submission deadline | March 15, 2020 |
Machine Learning, Deep Learning and Big Data are primarily changing the facets of data utilization especially in clinical healthcare. Various techniques, methodologies, algorithms are proposed by researchers to organize data in structured manner to assist the physicians in precision care of patients. Considering the modern trends and implementation of technologies powered via fusion of Big Data, Machine Learning and Data learning, the book is proposed to study their impact on healthcare analytics. This edited book is entirely based on the current research trends on Big Data, Deep Learning and Machine Learning applications pertaining to healthcare data. We know that healthcare data is highly critical for patient’s care and crucial for physicians. Healthcare data is generated in abundant manner with passage of time. To manage this data, the traditional techniques are not adequate, so new and advanced techniques are required to perform the tasks in efficient and secured manner. The main topics for the chapter for this book are:
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:
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Part A: Big Data in Healthcare Analytics
Chapter 1: Big Data in Healthcare Systems- Introduction, V’s, Challenges, Applications
Chapter 2: Foundations of Healthcare Informatics
Chapter 3: Advanced Decision-Making using Healthcare Data Analytics
Chapter 4 Emergence of Decision Support Systems in Healthcare
Chapter 5: Big Data based frameworks for Healthcare Systems
Chapter 6: Predictive Analysis and Modeling in Healthcare Systems
Chapter 7: Security and Privacy in Healthcare Systems
Chapter 8: Role of Social Media in Healthcare Analytics
Chapter 9: Big Data based Case Studies for Healthcare Analytics
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Smart Ambulance
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Semantic Framework in Healthcare
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Disease Prediction
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Electronic Health Records
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IoT and Big Data Integration in Healthcare for smart health monitoring
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Clinical Decision Support Systems
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Precision Medicine
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Smart Hospitals
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- Part B: Machine Learning, Deep Learning for Healthcare
- Chapter 1: Machine Learning and Deep Learning Paradigms in Healthcare Systems and Informatics
- Chapter 2: Machine Learning and Deep Learning frameworks for Healthcare Systems
- Chapter 3: Machine Learning and Deep Learning based Clinical Diagnostic Systems
- Chapter 4: Machine Learning and Deep Learning Algorithms for Healthcare Systems
- Chapter 5: ML and DL based case Studies
- Disease Identification and Drug Discovery
- Smart Operations Assistance
- Neurocritical Care
- Hospital Logistics
- Medical Imaging
Instructions for Submissions:
- Authors should take care of plagiarism and permitted similarity percentage is 10%
- All the accepted chapter would be indexed in all major indexes such as: Thomson/ISI, Scopus etc.
- There are no submission or acceptance fees for manuscripts submitted to this book publication.
- Chapter length should be in the range of 25 to 30 pages
- All manuscripts are accepted based on a double-blind peer review editorial process.
- All proposals should be submitted through the easychair online submission manager.
- References must be in APA style, otherwise, chapters will be returned to the authors for correction
Contact
All questions about submissions should be emailed to ...Dr. Anand Nayyar, anandnayyar@duytan.edu.vn; Mobile: +91-9878327635 (WhatsApp)