Introduction Text


In the field of health, “data and information” is called as evidence and the concept of “Evidence-based Medicine” is of great importance.In today's world, the amount of data produced, stored and processed in parallel with the developments in information and communication technologies is increasing incrementally. The fact that these data, which are produced in high sizes, cannot be stored and become meaningful by the classical methods have revealed the concept of “big data”.Processing and understanding of health data causes health services to be provided with better quality and planned according to the purpose, scientific studies to produce more reliable results and ease of physician services, health personnel to allocate more time to the patient and the awareness of patients. Currently, IoT devices, web-based, smart device supported and robotic products have been used in doctor assistant and patient service. The quality and quantity of available information and data accumulated from the development stage of these products directly related to human health to the usage stage is of great importance.The main objectives of this congress are to bring together the sciences that takes an active role in the production phase of modern technology and works in the back ofhouse, to increase the interaction, to ensure the use of common language and to ensure the sharingof products that convert the information to the product, and to create beginnings for new projects.


In line with these purposes, the objectives of the congress can be summarized in articles as follows:

  • To bring together the disciplines of “Data Science” which is an interdisciplinary science field
  • To introduce new products that can be realized with data in the field of health
  • To promote products developed on the basis of data
  • Creating collaborative work platforms
  • Launching new ideas and studies in the field of health
  • To identify problems related to storage, preparation and use of big data and to offer solutions
  • To bring together Industry and Academic studies
  • To follow the innovations regarding data ethics in the field of health and to offer suggestions
  • To introduce studies in the field of bioinformatics


Subject Titles


  • Data Science
  • Data Science in Health
  • Data Mining and Knowledge Discovery
  • Machine Learning
  • Artificial Neural Network
  • Deep Learning
  • Scientific Data Management
  • Data Engineering
  • Machine Learning and Deep Learning in Health Studies
  • Artificial Intelligence
  • Big Data Analytics and Metrics
  • Cloud Computing in Health
  • Data Base in Health
  • Social Networks
  • Big Data Ethics in Health
  • Data science in Drug Discovery
  • Wearables
  • Internet of Thinks
  • Data Science and Mathematics
  • Data Science and Statistics
  • CurrentAlgorithms
  • Bioinformatics
  • Data and Image Comprehension


The Language of Study: Studies may be in English or Turkish.

Announcement of the congress should be made to all universities. Besides, academicians from Bioengineering and Computer Engineering departments of Technical universities such as Gebze Technical University, Bogazici University, Yildiz Technical University, METU(for example Mustafa Murat COŞKUN who has presentations in an education platform named UDEMY and is graduated from METU may be invited.) In addition to these, people in private institutions should be invitedsuch as various Artificial Intelligence Centers(for example artificial intelligence centers of Istinye University and Uskudar University) which maintain their effectiveness in Turkey, Startup, Deeplearning Turkey.

The people who study in the subjects such as “Data Science, Big Data, Machine Learning, Deeplearning” in abroad should be identified and at least 4-5 person should be invited to the congress.

For example

Dr. Mehmet Kayaalp, Staff Scientist at NIH, USA (you can find detailed information online)

Suchlike people who can be invited from abroad should be invited by asking academicians in METU, Bogazici University, Yildiz Technical University, Gebze Technical University, so they may know better closely who can come.

The participants should be from these departments, utmost care should be taken on this.

  1. Computer Engineering
  2. Bioengineering
  3. Electric-Electronic Engineering
  4. Statistics/Biostatistics
  5. Bioinformatics
  6. Medicine
  7. Ethics
  8. Mathematics/Mathematics Teaching
  9. Other faculties/centers/departments related to Data Science in Health