City
Duration
Year
| Venue | Start Date | End Date | Net Fees | Details & Registration |
|---|---|---|---|---|
| Istanbul | August 11, 2025 | August 15, 2025 | 6100 GBP | PDF Register |
| Istanbul | September 15, 2025 | September 19, 2025 | 6100 GBP | PDF Register |
| Istanbul | October 13, 2025 | October 17, 2025 | 6100 GBP | PDF Register |
| Istanbul | November 17, 2025 | November 21, 2025 | 6100 GBP | PDF Register |
| Istanbul | December 22, 2025 | December 26, 2025 | 6100 GBP | PDF Register |
About corse
Artificial Intelligence (AI) has emerged as a transformative force in the healthcare sector, revolutionizing the way medical professionals diagnose, treat, and manage patient care. As healthcare systems strive for improved efficiency and patient outcomes, understanding how to leverage AI technologies becomes essential for professionals at all levels. This training course is designed to provide participants with in-depth knowledge about the various applications of AI in healthcare, including predictive analytics, machine learning, and natural language processing. By exploring real-world case studies and current trends, attendees will gain insights into how AI can streamline operations, enhance patient engagement, and facilitate data-driven decision-making. Throughout this comprehensive course, participants will engage in a collaborative learning environment where they can discuss challenges and opportunities in implementing AI solutions. The curriculum is structured to encompass theoretical frameworks as well as practical applications, ensuring that attendees not only grasp the foundational concepts but also acquire hands-on experience. By the end of the course, participants will be equipped with the skills necessary to drive innovation within their organizations and contribute to the ongoing evolution of healthcare delivery through AI technologies.The Objectives
- Understand the fundamentals of AI and its relevance to healthcare.
- Explore various AI technologies and their applications in healthcare settings.
- Analyze case studies demonstrating successful AI implementation.
- Identify challenges and ethical considerations in AI adoption.
- Develop a roadmap for integrating AI solutions in healthcare organizations.
- Foster collaborative discussions to share insights and experiences.
Training Methodology
The training will utilize a blend of instructional methods, including interactive lectures, group discussions, hands-on workshops, and case study analyses. Participants will work in teams to tackle real-world problems, encouraging collaboration and innovative thinking. This approach ensures a dynamic learning experience that caters to different learning styles.WHO SHOULD ATTEND
This course is ideal for healthcare professionals, including clinicians, administrators, data scientists, and IT specialists, who are interested in understanding and implementing AI technologies in their organizations. Additionally, policymakers and researchers seeking to explore the potential of AI in improving healthcare systems will find valuable insights in this program.Course Outlines
Day 1: Introduction to AI in Healthcare- Overview of artificial intelligence and its evolution
- Key concepts and terminologies in AI
- Current landscape of AI applications in healthcare
- Benefits of AI for healthcare providers and patients
- Challenges to AI integration in healthcare settings
- Ethical considerations and regulatory implications
- Types of healthcare data and their sources
- Importance of data quality and governance
- Data privacy and security issues
- Techniques for data collection and management
- Data analytics and its role in AI
- Case studies of data-driven decision-making in healthcare
- Introduction to machine learning concepts
- Types of machine learning algorithms used in healthcare
- Applications of predictive analytics in patient care
- Real-time monitoring and risk assessment
- Developing predictive models for healthcare outcomes
- Hands-on workshop: Building a simple predictive model
- Understanding natural language processing (NLP) and its significance
- Applications of NLP in electronic health records
- Challenges in processing medical language
- Sentiment analysis and patient feedback
- Automating documentation and administrative tasks
- Case study: Successful NLP implementations in healthcare
- AI applications in medical imaging and diagnostics
- Enhancing clinical decision support systems
- Personalized medicine and AI-driven treatment plans
- Integrating AI with existing clinical workflows
- Evaluating the effectiveness of AI solutions in practice
- Group discussion: Experiences with AI in diagnostics
Training Method?
- Pre-assessment
- Live group instruction
- Use of real-world examples, case studies and exercises
- Interactive participation and discussion
- Power point presentation, LCD and flip chart
- Group activities and tests
- Each participant receives a copy of the presentation
- Slides and handouts
Training Method?
The course agenda will be as follows:- Technical Session 30-10.00 am
- Coffee Break 00-10.15 am
- Technical Session 15-12.15 noon
- Coffee Break 15-12.45 pm
- Technical Session 45-02.30 pm
- Course Ends 30 pm
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