APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND MIXED AND AUGMENTED REALITY IN MEDICINE

ΕΦΑΡΜΟΓΕΣ ΤΕΧΝΗΤΗΣ ΝΟΗΜΟΣΥΝΗΣ ΚΑΙ ΜΙΚΤΗΣ ΚΑΙ ΕΠΑΥΞΗΜΕΝΗΣ ΠΡΑΓΜΑΤΙΚΟΤΗΤΑΣ ΣΤΗΝ ΙΑΤΡΙΚΗ

APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND AUGMENTED REALITY IN MEDICINE

COURSE CODEBE0902

COURSE INSTRUCTORTsougos Ioannis, Professor 

CO-INSTRUCTORSTsivaka Dimitra

ECTS:2.00

COURSE TYPE

EL | Background-Skills Development

TEACHING SEMESTERWINTER SEMESTER

WEEKLY TEACHING HOURS: 2 HOURS

Total Time (Teaching Hours + Student Workload)54 HOURS

PREREQUIRED COURSES:

NO

LANGUAGE OF TEACHING AND EXAMSENGLISH

AVAILABLE TO ERASMUS STUDENTSYES

SEMESTER LECTURES:DETAILS/LECTURES

TEACHING AND LEARNING METHODS :

Lectures in the amphitheater, education and practice in the laboratory.

Mandatory attendances to Lab exercises

Use of personal workstations (PCs) per person.

XR AUDIOVISUAL EQUIPMENT (AR and VR)

Communication with students through the educational platform e-class for the information of the students, the projection and distribution of the slides of the lectures, the provision of educational material the assignment and the reception of assignments to the students. 


STUDENT EVALUATION

Short answer questions,

Public presentation of work,

Problem solving.


Objective Objectives/Desired Results:

The course delves into the use of Artificial Intelligence technologies and their applications in the medical industry with an emphasis on decision support technologies.

Artificial intelligence in medicine refers to the use of technology such as machine learning and analytical algorithms to analyze data, diagnose diseases, provide personalized treatment and improve the quality of care.

Artificial intelligence can be used in many areas of medicine, such as evaluating images of medical examinations (such as X-rays and MRIs), predicting the course of disease, personalizing treatment, managing medical documents and improving the performance of clinical processes .

The application of artificial intelligence in medicine has the potential to improve the accuracy, efficiency and accessibility of health services.

The course material aims to understand the theory and methods related to the creation and operation of decision support systems and patient management. The different imaging modalities of anatomical information are presented. Concepts of remote medical care and practice, real-time monitoring of biomedical data on patients in and out of the clinic are introduced.

Finally, the aim of the course is the students’ understanding of the available possibilities provided by information and communication technology in the creation, storage, dissemination and use of structured medical knowledge as well as the demonstration of these possibilities in the facilitation of medical work. Augmented reality (AR) and virtual reality (VR) applications have wide application in medical education and can provide multiple benefits.

These topics will be presented through lectures, examples from real applications and laboratory exercise scenarios where students will apply their knowledge to real data.

Upon successful completion of the course the student will be able to:

The learning objectives of the course aim to understand the fundamental principles of artificial intelligence and machine learning, as well as the ability to apply these principles to medical problems.

  • Understanding the fundamentals of Artificial Intelligence (AI) and Machine Learning (ML): Students should understand the basic concepts and algorithms of AI and ML, such as neural networks, decision trees, and supervised/semi-supervised learning methods.
  • Applying AI and ML to medical data: Students should be able to apply AI and ML techniques to medical data, such as X-ray images, genetic analysis data and clinical patient histories.
  • Development of clinical applications: Students should be able to develop clinical applications based on AI and ML technologies, which address real problems in medical practice.
  • Evaluation of results: Students should be able to evaluate the effectiveness and accuracy of the models they develop, as well as recognize potential challenges and limitations.
  • Understanding AR and VR technology: Students should understand the basic principles and operation of AR and VR technology, as well as the differences between them.
  • Applications in medical education: Students should be able to recognize and explore the diverse applications of AR and VR technology in medical education, such as anatomy representation, surgical simulation, and clinical skills training.
  • Ethical and legal aspects: Students should be able to understand the ethical and legal aspects related to the use of artificial intelligence in medical practice.

The above learning objectives will help students develop the required knowledge, skills and abilities to successfully practice artificial intelligence in the medical field.

General Abilities

  • Research, analysis and synthesis of data and information, using the necessary technologies
  • Adaptation to new situations
  • Decision making
  • Autonomous work
  • Teamwork
  • Exercise criticism and self-criticism
  • Promoting creative and inductive thinking

Course URL :http://eclass.uth.gr/eclass/courses/SEYA 274 /

Course Description:
  1. Introduction to artificial intelligence and machine learning.
  2. Applications of artificial intelligence in medicine.
  3. Data analysis in medicine: Methods and tools.
  4. Machine learning models for medical data analysis.
  5. Applications of augmented reality and virtual reality in medical education.
  6. Physiological signal and image processing technologies for medical applications.
  7. Ethical and legal aspects of artificial intelligence in medicine.
 
Recommended reading:

-Proposed Bibliography:

“Artificial Intelligence in Medicine: What is important?” από Sussman, A. και McCue, M. J. 

“Artificial Intelligence in Medicine: Future Prospects” από Deka, G. C. και Choudhury, P..

– –Related scientific journals: –

 


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