Artificial Intelligence in health
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It harnesses the power of the TOSC Model: Technology, Organization, Skills and Culture – a comprehensive approach covering the critical dimensions of digital implementation.
Courses in this learning path:
1. Introduction to Artificial Intelligence for Healthcare
This introductory course focuses on the basic principles of AI and its role and potential in healthcare.
Objectives:
• Understand the basics of artificial intelligence and its potential applications in healthcare.
Duration: 4 weeks
2. Introductory course of Artificial Intelligence in medicine
Course accredited by the College of Doctors Romania.
Hybrid format: online and physical at the headquarters of the MAVIS Technological Transfer Center, str. Grigore Ghica Vodă no. 13, Nicolae Leon building, 12th floor.
Identified training requirements: The need for doctors to constantly update their knowledge in the context of technological development and the increasingly frequent use of Artificial Intelligence in medicine.
The analysis of these requirements and the motivation of the organization: Artificial intelligence is one of the innovations in the field of new medical technologies and has a major contribution in the management of the patient, but also of the hospital.
Expected results: Participants will familiarize themselves with the current situation regarding the implementation of artificial intelligence in medicine, both in general and specific to medical fields. They will receive information and gain knowledge about the limits of the use of AI in medicine and possible ethical slippages.
Pursued educational objective: Development of skills in the use of artificial intelligence resources in medicine.
Date held:
• 19 september 2024, 14.00 – 19.30
3. Digital transformation in Public Health Institutions
Course accredited by the College of Doctors Romania.
Hybrid format: online and physical at the headquarters of the MAVIS Technological Transfer Center, str. Grigore Ghica Vodă no. 13, Nicolae Leon building, 12th floor.
Identified training requirements: The need for doctors to constantly update their knowledge in the context of technological development and the evolution of the health system.
The analysis of these requirements and the motivation of the organization: It derives from the need to align the staff of public health institutions to the new technologies and digital practices.
Expected results: Participants will be prepared to manage and contribute to digital transformation in public health institutions, bringing significant benefits to both professionals and patients
Educational objective: Familiarize participants with the key concepts of digital transformation, develop skills to implement digital technologies in medical practice, and understand the impact on improving medical services and patient outcomes.
Date held:
15 october 2024, 14.00 – 19.30
4. Understanding medical data
This course will provide a comprehensive understanding of different types of medical data such as structured, unstructured data, images and genomics.
Objectives:
• Gain an understanding of different types of medical data and their significance in AI applications.
Duration: 4 weeks
5. The basics of Machine Learning
This course will provide an introduction to the principles, techniques, and applications of machine learning.
Objectives:
• Understand the fundamental principles and techniques of Machine Learning
Duration: 8 weeks
6. AI for medical imaging
This specialized course will focus on how AI can help medical imaging, including detecting abnormalities and aiding in diagnosis.
Objectives:
• Understand how AI is used in medical imaging and can apply AI techniques to analyze medical images.
Duration: 12 weeks
7. AI for clinical decision making
This course will focus on how AI can assist in clinical decision making, improving diagnoses and treatment plans.
Objectives:
• Learn how to use artificial intelligence to aid clinical decision-making processes.
Duration: 8 weeks
8. AI and personalized medicine
This course will delve into how AI can enable personalized medicine, providing personalized healthcare based on an individual’s genetic makeup, lifestyle and environment.
Objectives:
• Understand how AI can contribute to personalized medicine.
Duration: 8 weeks
9. Ethical considerations and bias in health AI
This course will explore the ethical considerations and potential biases that can occur when using AI in healthcare.
Objectives:
• Understand the ethical implications and potential biases of using AI in healthcare.
Duration: 4 weeks
10. The AI project in the field of health
A final project that requires the application of skills and knowledge gained in previous courses to a real-world healthcare challenge.
Objectives:
• Apply AI techniques to solve a real-world healthcare problem.
Duration: 8 weeks
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