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Special Session 2

Health Analytics: From Data to Insights

This special session aims to shed light on Health Analytics, which is the process of using data- driven approaches to gain meaningful insights and inform decision-making in the healthcare industry. It involves collecting, organizing, and analyzing vast amounts of healthcare data from various sources, such as electronic health records, medical imaging, wearable devices, and clinical trials. The ultimate goal of health analytics is to transform raw data into actionable insights that can lead to improved patient outcomes, better resource allocation, and more efficient healthcare delivery. Key steps in the health analytics process include data collection, data cleaning, data integration, and data analysis. Health data can be both structured (e.g., lab results, patient demographics) and unstructured (e.g., clinical notes, medical literature), necessitating sophisticated techniques like natural language processing (NLP) to extract valuable information from unstructured sources. Data analysis techniques commonly used in health analytics encompass statistical analysis, machine learning, and artificial intelligence. These methods aid in identifying patterns, trends, and correlations within the data, which can be used to predict disease risk, enhance diagnostic accuracy, optimize treatment plans, and even discover new drugs or therapies. Health analytics plays a crucial role in precision medicine, which tailors treatments to individual patients based on their genetic makeup, lifestyle, and other factors. By analyzing large datasets, health analytics enables healthcare providers to offer personalized and more effective care, leading to improved patient satisfaction and health outcomes. Moreover, health analytics supports population health management and public health initiatives. It helps public health officials track disease outbreaks, identify high-risk groups, and design targeted interventions to prevent the spread of infections and promote healthier communities. However, health analytics comes with its challenges, particularly regarding data privacy and security. Healthcare data is highly sensitive, and it is essential to adhere to strict privacy regulations to protect patients' confidentiality while still allowing for data sharing in research and analysis. The special session is an endeavour to present health analytics as a powerful tool that transforms vast amounts of healthcare data into valuable insights, ultimately leading to more informed decisions, improved patient care, and advancements in medical research. As technology and data science continue to evolve, health analytics will undoubtedly play an increasingly vital role in shaping the future of healthcare.

The Session accepts papers on topics that are not limited to::

● Electronic Health Records (EHR) and Data Integration
● Electronic Health Records (EHR) and Data Integration
● Predictive Analytics for Disease Diagnosis
● Drug Discovery and Development
● Precision Medicine
● Health Monitoring and Wearable Devices
● Healthcare Image Analysis
● Natural Language Processing (NLP) in Healthcare
● Patient Outcome Prediction
● Fraud Detection in Healthcare
● Public Health Analytics
● Data Privacy and Security in Healthcare
● Healthcare Data Visualization
● Telemedicine and Remote Patient Monitoring
● Ethical Considerations in Healthcare Data Science
● Data Science in Health Policy and Planning
● Clinical Decision Support Systems (CDSS)
● Healthcare Data Quality and Integration
● Real-time Monitoring and Surveillance.
● Healthcare Performance Metrics and KPIs
● Healthcare Data Mining
● Healthcare Predictive Modeling
● Patient Segmentation and Cohort Analysis
● Social Determinants of Health Analysis.
● Healthcare Cost Analysis and Resource Optimization
● Ethical Considerations in Health Analytics

Important Information:

Session Chairs

Prof. Juergen Seitz, Department of Business Information Systems, Baden-Wuerttemberg Cooperative State University Heidenheim, Heidenheim, Germany
Prof. Nilmini Wickramasinghe, La Trobe University, Melbourne, Australia

Important Dates:

Call for paper begins : 01/07/2023
Last date of paper submission : 31/07/2023
Author Notification : 25/10/2023
Early Bird Registration Closes : 31/10/2023
Camera Ready Copy & Copy Right submission : 31/10/2023
Conference Start : 19/01/2024

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Special Session Brochure

Conference Proceeding by

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Important Dates


Registration Closes


Last Date for Paper Submission


Author Notification


Early Bird Registration Closes


Camera Ready Copy & Copy Right Submission

Latest News

AISC Series of Springer Book as proceedings of ICDMAI 2020 is available on Volume 1 - https://link.springer.com/book/10.1007/978-981-15-5616-6 Volume 2 - https://link.springer.com/book/10.1007/978-981-15-5619-7

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