Data Analytics and Spatial Data Modeling Application and Research Center

Data Analytics and Spatial Data Modeling Application and Research Center (VAM) was established in 2020 with the aim of designing, analyzing and implementing large-scale data analytics systems needed by researchers and organizations, especially in health, environment, engineering and finance.

As VAM, our primary goal is to produce policies for the public good that aim to produce sustainable solutions to regional, national and international problems with big data analytics applications.

Data Analytics and Spatial Data Modeling provide the basis for supporting decision-making processes in various sectors, identifying risks, increasing operational efficiency and contributing to sustainability principles, as well as the effective use of innovative technologies such as artificial intelligence in the healthcare sector. Therefore, the use of these technologies is becoming even more important.

The main methods that offer a wide range of analysis and modeling in the studies carried out in these areas are as follows:

• Data Mining

• Machine Learning

• Deep Learning

• Spatial Analysis

• Optimization

• Statistical Analysis

The Data Analytics and Spatial Data Modeling Application and Research Center carries out various activities to support and advance important studies in these fields. Our center was established to collaborate with universities, public institutions and the private sector in projects using data analytics and spatial data modeling techniques and to encourage scientific research.

The objectives of our center are as follows:

• To develop and implement joint projects in the field of data analytics and spatial data modeling in cooperation with universities, public institutions and private sector.

• To research and develop new data analytics and spatial data modeling techniques and to make these techniques usable in industrial and academic environments.

• To organize conferences, seminars and workshops in cooperation with similar centers at national and international level and to encourage knowledge sharing in this field.

• To contribute to the scientific literature in the field of data analytics and spatial data modeling and to support research in this field.

Our center organizes various events to follow the latest developments in the field of data analytics and spatial data modeling and to bring together experts in this field. It also supports the development of young talents in this field by offering training programs and internship opportunities for students.

In the near future, many scientific activities are being planned under the leadership of our centers in order to achieve our national goals in this field, to act jointly and to provide a working environment:

• Conducting the II International Congress on Artificial Intelligence in Health online,

• The journal Artificial Intelligence Theory and Applications started to be published,

• Increasing collaborations with the International Association for Artificial Intelligence in Health,

• To organize mini workshops to increase the recognition of the center on a local and national scale and to bring together academics working in this field.

The research areas of the Data Analytics and Spatial Data Modeling Application and Research Center can be shaped according to the goals, areas of expertise and needs. The main research areas consisting of various disciplines are as follows:

• Big Data Analytics and Data Mining

• Analyzing Health Data

• Personalized Medicine and Health Care

• Burden of Disease Estimation

• Air Pollution and Health Relationship Analysis

• Risk Profile Analysis of Disease Areas

• Accessibility and Efficiency of Health Services

• Patient Medical History Analysis

• Analysis of Disease and Environment Interaction

• Cost-Effect Analysis of Health Services

• Integration and Standardization of Health Data

• Patient Circulation and Mobility Analysis

• Hospital and Health Center Positioning Analysis

• Vaccine Distribution Strategies

• Disease Control and Public Health Strategies

• Patient Demographic Analysis

• Health Resources Utilization Efficiency Analysis

• Effects of Environmental Factors on Health

• Cancer Mapping and Monitoring

• Mental Health and Spatial Analysis

• Crisis Management and Emergency Health Services

• Nutrition and Health Relationship Analysis

• Training and Resource Distribution

• Spatial Data Analytics and Geographic Information Systems

• Business Intelligence and Decision Support Systems

• Transportation and Logistics Optimization

• Energy Efficiency and Resource Management

• Environmental Analysis and Sustainability