AI in Healthcare Systems

AI in Healthcare Systems

Introduction

Healthcare systems worldwide are under increasing pressure to deliver better patient outcomes, higher operational efficiency, cost control, and regulatory compliance, while managing growing data volumes and workforce shortages. Artificial Intelligence (AI) is emerging as a powerful enabler to support healthcare organisations across clinical support, operations, research, administration, and strategic planning.

Advances in Machine Learning, Large Language Models (LLMs), and Generative AI have expanded AI adoption beyond data scientists and clinicians. Today, healthcare professionals, administrators, analysts, and leaders can directly use AI tools to summarise medical literature, analyse operational data, improve patient communication, support reporting, and enhance decision-making.

This course provides a practical, business-focused introduction to AI for healthcare professionals. Participants will learn AI fundamentals, understand how AI technologies interconnect, and gain hands-on experience with leading AI tools such as ChatGPT, Gemini, Copilot, Perplexity, Grok, Claude, Manus, DeepSeek, Qwen, and NotebookLM. The emphasis is on responsible, ethical, and compliant use of AI, real healthcare use cases, and measurable productivity improvements, without involving medical diagnosis or requiring programming skills.

Who Should Attend

This course is designed for working professionals in healthcare-related environments, including:

Healthcare administrators and managers
Hospital operations and quality teams
Health information management professionals
Public health and healthcare analysts
Medical research and clinical support staff
Health insurance and payer organisations
Digital health and transformation teams
Healthcare leaders and decision-makers

This course is not intended for clinical diagnosis or treatment decision-making. No prior AI or technical background is required.

Level: Beginner to Intermediate. No prior AI or technical background is required.

Delivery Mode: 2-days, In-house. Instructor-led, hands-on AI tools (no coding required).

Outcome

By the end of this course, participants will be able to:

Understand core AI concepts and terminology relevant to healthcare
Distinguish between AI, Machine Learning, Deep Learning, LLMs, and Generative AI
Evaluate and select AI tools suitable for healthcare operations and research support
Apply AI tools to healthcare reporting, analysis, communication, and documentation
Use AI responsibly within ethical, privacy, and regulatory constraints
Identify high-impact AI use cases across healthcare systems
Contribute to AI adoption and digital transformation initiatives in healthcare organisations

Select to design your own content and request for a customized quotation

No	Topic	Topic Description
1	Understanding AI in Healthcare	What Artificial Intelligence is and is not Relationship between: Artificial Intelligence Machine Learning Deep Learning Large Language Models Generative AI How AI systems learn from healthcare data Current AI applications in healthcare: clinical decision support (non-diagnostic) patient engagement and communication healthcare operations and resource planning medical research and literature review Strengths and limitations of AI in healthcare environments
2	AI Tools Landscape for Healthcare Professionals	Overview of modern AI tools used in healthcare: ChatGPT, Gemini, Copilot, Claude Perplexity, Grok, Manus, DeepSeek, Qwen, NotebookLM Differences in: research summarisation vs operational analysis reasoning accuracy and reliability privacy, patient data protection, and confidentiality Selecting the right AI tool for: healthcare documentation and reporting patient education materials internal knowledge management Prompt engineering fundamentals for healthcare use cases Hands-On Activities Summarising healthcare reports and guidelines using AI Drafting patient-friendly educational content Comparing outputs across multiple AI tools
3	AI for Healthcare Operations and Reporting	AI-assisted analysis of healthcare operations: patient flow and capacity planning staffing and resource utilisation appointment and scheduling efficiency AI-supported performance dashboards and reporting Using AI with spreadsheets: Excel with Copilot Google Sheets with Gemini Translating operational data into management insights Hands-On Activities Generating operational insights using AI tools Drafting executive healthcare reports
4	Responsible AI, Ethics, Privacy, and Compliance in Healthcare	Ethical risks of AI in healthcare: bias and fairness misinformation and hallucinations over-reliance on AI outputs Patient data privacy and confidentiality considerations Regulatory and governance principles (high-level) Human-in-the-loop decision-making models Best practices for responsible AI usage in healthcare
5	AI for Healthcare Analytics and Research Support	AI-assisted medical literature review and synthesis Supporting public health and population health analysis AI for outcomes tracking and reporting (non-clinical) Using AI to support evidence-based decision-making Hands-On Activities Summarising research papers using AI Generating structured research insights
6	AI for Patient Engagement and Communication	AI-assisted patient communication and education Creating clear, non-technical health information Supporting call centres and administrative workflows Knowledge-based AI using internal documents: NotebookLM and Manus Hands-On Activities Drafting patient communication materials Designing an AI-supported patient information workflow
7	AI-Enabled Workflow Automation in Healthcare	Designing AI-supported healthcare workflows: data → analysis → reporting → decisions Integrating AI tools into healthcare operations Improving coordination between departments Measuring productivity, quality, and service impact Exercise Designing an AI-supported healthcare workflow
8	AI Strategy for Healthcare Leaders and Decision-Makers	Identifying high-impact AI opportunities in healthcare systems Build vs buy vs partner considerations Developing an AI adoption roadmap for healthcare organisations Establishing AI governance, ethics, and oversight structures Preparing healthcare teams for AI-enabled ways of working Workshop Drafting a high-level AI strategy for a healthcare organisation

Expert

Dr. Mohammed Muayad Abdulrazzaq

Dr. Mohammed Muayad Abdulrazzaq, fondly known as Dr. Obay is an accomplished AI Trainer, Academic Leader, TEDx Speaker, Industry Advisor, and Entrepreneur, internationally recognised for his contributions to Artificial Intelligence education, research, and innovation. Holding a Ph.D. in Artificial Intelligence and bringing over 20 years of experience across the information technology landscape, Dr. Obay’s expertise spans AI, Big Data Science, Machine Learning, Deep Learning, Generative AI, Large Language Models (LLMs), and Immersive Technologies. As a certified and HRD Corp-accredited trainer, Dr. Obay has trained more than 5,000 professionals, students, and business leaders through highly practical and results- driven programs in Data Science, AI Engineering, Generative AI, and LLMs. His workshops are widely praised for their clarity, relevance, and ability to translate complex AI concepts into real-world business impact. Recently, Dr. Obay was honoured to begin a new chapter as an Industry Advisor at ICMS, contributing to advanced programs and professional certifications in Generative AI, Large Language Models, Google AI & Machine Learning, and Microsoft Azure AI. His advisory role bridges academia and industry by empowering future-ready talent and organisations to thrive in the era of intelligent automation. Recognised for his excellence in AI education and leadership, Dr. Obay serves as an ELITE Fellow at the University of Malaya (UM) — Malaysia’s top-ranked university — and as an Adjunct Associate Professor at Taylor’s University, where he supervises Ph.D. and Master’s students at Taylor’s University and the International Islamic University Malaysia (IIUM). His academic work focuses on applying AI to solve real- world problems while shaping the next generation of innovators. An entrepreneur at heart, he is the Founder of Artificial Intelligence & Coding for All (AIC4ALL) — a global learning platform that equips learners of all ages with essential skills in AI, coding, and data science for IR 4.0 & IR 5.0. He also leads INNOEYETIVE, a digital innovation agency leveraging AI, Big Data, and Immersive Tech to accelerate digital transformation. As a TEDx and international speaker, Dr. Obay has delivered impactful talks and keynotes that demystify AI, inspire innovation, and promote ethical adoption of emerging technologies. His lifelong mission is simple yet powerful — to empower professionals, educators, and leaders worldwide to harness the transformative power of AI for a better, smarter future.