Background: AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. Machine learning has the potential to impact every area of medicine, bringing with it the possibilities of cheaper, more accurate, more accessible treatment. As a result, the demand for professionals with both AI skills and medical knowledge has never been greater. Medical professionals need to be adequately trained in this technology, its advantages to improve cost, quality, and access to health care.

Objective: This workshop aims to introduce key AI concepts to professionals in the field of medical, to be comfortable in engaging with AI in their clinical careers. No technical background is required.

Structure of the workshop: Participants will learn about concepts of Artificial Intelligence, Machine Learning, and data-driven decision making. Thirty percent of the time will be spent on lectures introducing the concepts. The rest will be hands-on experiment applying the concepts to real-world data.

After completing the course, the attendees should be able to:

• Have a strong sense of what AI is and how it is used in the field of medicine
• Compare and select relevant AI methods for the development of AI applications in healthcare
• Reflect on obstacles and driving factors for how AI-based solutions can be applied in healthcare
• Learn basics of the most popular programming language in the field of AI: Python

Duration: 4 hours

Who should Attend?

• Faculty and researchers in the field of medical, working on research projects that demand knowledge of AI methodologies
• Clinical practitioners who want to enhance their knowledge about AI
• Recent radiography graduates, radiology managers, radiography researchers and educators who wish to further their understanding of the basic principles and applications of AI in Radiography and Medical Imaging
• Anyone who is interested to explore the filed of Artificial Intelligence

Required Equipment: A computer with internet connection

Workshop Facilitator: Prof. Farah Magrabi 

Professor of Biomedical and Health Informatics
Co-chair, Safety, Quality, and Ethics Working Group, Australian Alliance for Artificial Intelligence in Healthcare (AAAiH)
Centre for Health Informatics
NHMRC Centre for Research Excellence in Digital Health
Australian Institute of Health Innovation
Macquarie University, Australia 

Workshop: Implementing artificial intelligence (AI) for clinical decision support in real-world settings

Background: Despite the widespread enthusiasm for artificial intelligence (AI) and machine learning (ML) in healthcare, adoption and routine use in clinical settings remains slow. Healthcare organisations are increasingly developing ML-enabled clinical decision support systems in-house, and are also being approached by commercial vendors to co-develop or purchase AI tools.

Objective: The goal of this workshop is to introduce the general principles of evaluating AI in clinical decision support.

Structure of the workshop: Participants will learn how to select and implement ML-enabled clinical decision support systems in a hospital setting. The learning objectives are to:

1. Assess needs for AI in clinical decision-support.
2. Describe general principles for evaluating ML-enabled clinical decision support systems.
3. Formulate a plan to select and implement AI tools in a hospital setting.

Duration: 4 hours

Who Should Attend? 

1. Health care providers/organizations
2. Clinicians
3. Hospital executives
4. Managers
5. Researchers who are studying the impact of AI or any other digital technology on care delivery and patient outcomes
6. IT personnel who are involved in choosing and implementing digital health technologies.

Workshop Facilitator: Prof. Dr. Shabbir Syed-Abdul

Professor of Artificial Intelligence & Digital Health

Graduate Institute of Biomedical Informatics

Adjunct Professor at School of Gerontology and Long-Term Care

Taipei Medical University

Workshop: The Role of Wearable sensors in the long-term care and telemonitoring of Patients with Chronic Diseases

Background Ubiquitous progress in wearable sensing and mobile-computing technologies, alongside growing diversity in sensor modalities, has created new pathways for the collection of health and well-being data outside of laboratory settings, in a longitudinal fashion. Wearable and mobile devices have the potential to provide low-cost, objective measures of physical activity, clinically relevant data for patient assessment and scalable behavior monitoring in large populations. This data can be used in both interventional and observational studies to derive insights regarding the links between behavior, health, and disease, as well as to advance the personalization and effectiveness of com- medical wellness applications.

Objective: This workshop will discuss challenges and opportunities of Wearable sensors in the long-term care and telemonitoring of Patients with Chronic Diseases.

Structure of Workshop:

Group discussion, and presentation by each group

Who Should Attend?

• Doctors
• Medical students
• Postgraduate
• Researchers
• Hospital administrators

Intended Outcomes: After this workshop, participants will be able to understand the need and usefulness of the werable devices. What are the implementation challenges? How to deal with those challenges.

Duration: 4 hours

Venue: PC Lab 2 Ground Floor

Health Sciences Center

Kuwait University

Background: AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. Machine learning has the potential to impact every area of medicine, bringing with it the possibilities of cheaper, more accurate, more accessible treatment. As a result, the demand for professionals with both AI skills and medical knowledge has never been greater. Medical professionals need to be adequately trained in this technology, its advantages to improve cost, quality, and access to health care.

Objective: This workshop aims to introduce key AI concepts to professionals in the field of medical, to be comfortable in engaging with AI in their clinical careers. No technical background is required.

Structure of the workshop: Participants will learn about concepts of Artificial Intelligence, Machine Learning, and data-driven decision making. Thirty percent of the time will be spent on lectures introducing the concepts. The rest will be hands-on experiment applying the concepts to real-world data.

After completing the course, the attendees should be able to:

• Have a strong sense of what AI is and how it is used in the field of medicine
• Compare and select relevant AI methods for the development of AI applications in healthcare
• Reflect on obstacles and driving factors for how AI-based solutions can be applied in healthcare
• Learn basics of the most popular programming language in the field of AI: Python

Duration: 4 hours

Who should Attend?

• Faculty and researchers in the field of medical, working on research projects that demand knowledge of AI methodologies
• Clinical practitioners who want to enhance their knowledge about AI
• Recent radiography graduates, radiology managers, radiography researchers and educators who wish to further their understanding of the basic principles and applications of AI in Radiography and Medical Imaging
• Anyone who is interested to explore the filed of Artificial Intelligence

Required Equipment: A computer with internet connection

Workshop Facilitator Prof. Nabil Zary

Senior Director, Professor of Medical Education

Institute for Excellence in Health Professions Education

MBRU, Healthcare City, Dubai, UAE

Workshop: Artificial Intelligence in Health Professions Education: A Practical Guide

Background: Artificial Intelligence (AI) has evolved throughout the years, developing rapidly in several aspects, with the recent advances in deep learning and artificial neural networks. AI, the term coined by John McCarthy in 1955, is defined as a machine exhibiting intelligent behavior, which includes perceiving, reasoning, learning, or communicating as well as the ability to perform human tasks. AI is a spectrum that consists of, but is not limited to, the following: machine learning, computer vision, natural language processing, and pattern recognition. Over the past 30 years, there have been significant developments of AI in education, better known as Artificial Intelligence in Education. Advances such as teacher bots: teaching assistants tasked to support content delivery, provide feedback, and manage supervision are applications of AI in education. The increased interest in the application of AI in health sciences education brings its own set of challenges. As the degree of digitalization in medical curricula increases, it is therefore timely to provide participants with an opportunity to understand and actively consider leveraging AI in health sciences education.

Who Should Attend?

• Anyone interested in using Artificial Intelligence in Health Sciences Education is invited to participate.
• Individuals involved with planning, design, development, and implementation of technology enabled/enhanced innovations are encouraged to attend.

Structure of Workshop: The workshop will start with

1. An overview of the current state of AI in health sciences education,
2. Followed by small group interactive activities to increase participants’ overall understanding of AI in education.
3. Two further large and small group exercises will allow participants to apply key concepts related to the planning of an AI project, targeting
   1. Curriculum
   2. Learning
   3. Assessment

Intended Outcomes: After this workshop, participants will be able to

• Identify key elements specific to understanding artificial intelligence in health sciences education,
• Describe an approach to designing AI enabled conversational agents
• Outline common strategies and challenges when planning and evaluating AI projects.

Level: Introductory/Intermediate, Duration: 4 Hours

Venue: PC Lab 1 Ground Floor

Health Sciences Center, Kuwait University

Background: AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. Machine learning has the potential to impact every area of medicine, bringing with it the possibilities of cheaper, more accurate, more accessible treatment. As a result, the demand for professionals with both AI skills and medical knowledge has never been greater. Medical professionals need to be adequately trained in this technology, its advantages to improve cost, quality, and access to health care.

Objective: This workshop aims to introduce key AI concepts to professionals in the field of medical, to be comfortable in engaging with AI in their clinical careers. No technical background is required.

Structure of the workshop: Participants will learn about concepts of Artificial Intelligence, Machine Learning, and data-driven decision making. Thirty percent of the time will be spent on lectures introducing the concepts. The rest will be hands-on experiment applying the concepts to real-world data.

After completing the course, the attendees should be able to:

• Have a strong sense of what AI is and how it is used in the field of medicine
• Compare and select relevant AI methods for the development of AI applications in healthcare
• Reflect on obstacles and driving factors for how AI-based solutions can be applied in healthcare
• Learn basics of the most popular programming language in the field of AI: Python

Duration: 4 hours

Who should Attend?

• Faculty and researchers in the field of medical, working on research projects that demand knowledge of AI methodologies
• Clinical practitioners who want to enhance their knowledge about AI
• Recent radiography graduates, radiology managers, radiography researchers and educators who wish to further their understanding of the basic principles and applications of AI in Radiography and Medical Imaging
• Anyone who is interested to explore the filed of Artificial Intelligence

Required Equipment: A computer with internet connection

Workshop Facilitator:  Prof. Amine Choukou

University of Manitoba, Canada

Associate Professor

Department of Occupational Therapy, College of Rehabilitation Sciences University of Manitoba

Canada

Workshop Title: Determinants of AI implementation in rehabilitation 

Background: The application of AI has been identified as a priority for rehabilitation.

Objective: This workshop aims to

1) Initiate an academic discussion to identify priorities for the next chapter of rehabilitation,

2) Establish a framework for implementing AI in rehabilitation, and

3) Identify the associated research gaps and determine future direction.

Who should Attend: This workshop is open to

• Faculty
• Managers
• Clinicians
• Students with experience and/or interest in incorporating AI into rehabilitation processes and procedures.

Structure of Workshop:

A combination of facilitated discussion about novel applications of AI in rehabilitation, interactive subgroup exercises, and sharing of resources and results will provide the rehabilitation community with a roadmap for implementing AI in rehabilitation in the Kuwaiti health ecosystem.

Intended Outcomes: After this workshop, participants will be able to

• Will have the opportunity to share their lived experience and perceptions of the role of AI in rehabilitation
• Discuss barriers and opportunities for embracing AI in clinical practice and challenges and opportunities for training and leveraging expertise among the existing workforces.

Duration: 4 hours

Venue: PC Lab 2 Ground Floor

Health Sciences Center

Kuwait University