COURSE UNIT TITLE

: BIG DATA IN HEALTHCARE AND NEW APPROACHES

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
SHS 2051 BIG DATA IN HEALTHCARE AND NEW APPROACHES ELECTIVE 2 0 0 3

Offered By

Vocational School of Healthcare

Level of Course Unit

Short Cycle Programmes (Associate's Degree)

Course Coordinator

DOCTOR MINE INANÇ

Offered to

Medical Laboratory Techniques
Oral and Dental Clinical
Anesthesia
Medical Documentation and Secretariat
Audiometry
Medical Imaging Techniques
First And Emergency Aid
Nuclear Medicine Techniques
Radioterapy

Course Objective

The aim is to introduce students to the significance, management, and applications of big data in healthcare. This includes examining how big data is utilized in the healthcare sector, how it is integrated into digital transformation processes, and addressing the ethical and legal issues in healthcare from a holistic perspective. The goal is to equip students with the skills to develop innovative solutions for both individual and societal health issues by using big data analytics techniques and emerging approaches.

Learning Outcomes of the Course Unit

1   1. Can define the concept of big data and relate it to healthcare contexts through practical examples.
2   2. Can discuss the significance of big data, the Internet of Things (IoT), machine learning, artificial intelligence, and other methods in the healthcare sector.
3   3. Can evaluate the integration of new digital technologies such as telemedicine, wearable technologies, and electronic health records into healthcare services, and their relationship with big data.
4   4. Can critically analyze current examples of artificial intelligence-supported early diagnosis, preventive health policies, and personalized medicine, offering a critical perspective on these approaches.
5   5. Can analyze the importance of data privacy, sharing, ethical principles, and legal regulations in the context of healthcare data, demonstrating an understanding of data security and ethical responsibilities.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to the Concept of Big Data
2 The Concept of Big Data in Healthcare
3 Digital Transformation in Healthcare and Stakeholders in the Digital Ecosystem
4 Data Platforms and Cloud Computing
5 Internet of Things (IoT)
6 Artificial Intelligence
7 Machine Learning
8 The Contribution of Big Data to Decision-Making Processes
9 Personalized Medicine and Big Data
10 Preventive Health Applications
11 Digital Health Applications with Big Data
12 Current Technological Trends (IoT, Blockchain, Next-Generation Analytics)
13 The Ethical Dimensions of Digital Data
14 Big Data Applications and Case Study Analyses

Recomended or Required Reading

Prof.Dr. Necmi Gürsakal, Büyük Veri, Dora Yayınları, 2021, ISBN: 9786052472866
- Ed. Hakan Ertin, Tuncay Sandıkçı, Sağlık Alanında Büyük Veri, Isar Yayınları, 2020, ISBN: 9786059276207
-Prof.Dr. Sezer Korkmaz, Fırat Seyhan, Sağlıkta Yapay Zeka ve Dijital Hastaneler, Siyasal Kitabevi, 2024. ISBN:9786256586222
- Jülide Güzin Karagöz, Sağlıkta Dijital Dönüşüm, Yapay Zeka ve Nesnelerin Interneti (IoT), Kutlu Yayınevi, 2018, ISBN: 9786056837647
- Ed. Prof. Dr. Hakkı Muammer Karakaş, Büyük Veri, Endüstriyel Internet ve Sağlık Alanındaki Uygulamaları,Betim Kitaplıığı Yayınevi, 2016, ISBN: 9786058695740

Planned Learning Activities and Teaching Methods

Lecture with visual and written material

Assessment Methods

To be announced!

Further Notes About Assessment Methods

None

Assessment Criteria

presantation and exam

Language of Instruction

Turkish

Course Policies and Rules

Fundamentals of Application is made within the framework of the SHMYO and examinations and evaluated.

Contact Details for the Lecturer(s)

Lecturer Dr. Mine INANÇ;
e-mail: mine.inanc@deu.edu.tr;
Tel: 0 (232) 412 9865

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Group session 14 2 28
Lectures 14 2 28
Preparing presentations 7 2 14
Preparation for final exam 1 1 1
Project Final Presentation 1 1 1
Final 1 1 1
TOTAL WORKLOAD (hours) 73

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12
LO.1
LO.2
LO.3
LO.4
LO.5

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

Copyright 2015 DEÜ. BİD

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