AI in Healthcare

• Basic understanding of machine learning concepts
• Experience with Python programming
• Familiarity with healthcare data or clinical workflows is beneficial

Audience

• Healthcare professionals interested in AI applications
• Data scientists and AI engineers working in healthcare
• Technology leaders and decision-makers in the medical field

Artificial Intelligence (AI) is transforming healthcare by enhancing patient care, improving diagnostics, and optimizing hospital workflows. AI in Healthcare explores the current and future applications of AI, focusing on its role in solving healthcare challenges while ensuring ethical and safe implementation.

This instructor-led, live training (online or onsite) is aimed at intermediate-level healthcare professionals and data scientists who wish to understand and apply AI technologies in healthcare environments.

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

• Identify key healthcare challenges that AI can address.
• Analyze AI’s impact on patient care, safety, and medical research.
• Understand the relationship between AI and healthcare business models.
• Apply fundamental AI concepts to healthcare scenarios.
• Develop machine learning models for medical data analysis.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to AI in Healthcare

• Overview of AI and machine learning in medicine
• Historical development of AI in healthcare
• Key opportunities and challenges in AI adoption

Healthcare Data and AI

• Types of healthcare data: structured and unstructured
• Data privacy and security regulations (HIPAA, GDPR)
• Ethical considerations in AI-driven healthcare

Machine Learning Fundamentals for Healthcare

• Supervised vs. unsupervised learning
• Feature engineering and data preprocessing for medical datasets
• Evaluating AI models in healthcare applications

AI Applications in Patient Care

• AI in medical imaging and diagnostics
• Predictive analytics for patient outcomes
• Personalized medicine and treatment recommendations

AI for Hospital and Clinical Operations

• Automating administrative tasks with AI
• AI-driven decision support systems
• Optimizing hospital resource management

Ethics, Bias, and AI Governance in Healthcare

• Understanding bias in medical AI models
• Regulatory and compliance considerations
• Ensuring transparency and accountability in AI systems

Capstone Project: AI-Driven Patient Data Analysis

• Exploring a healthcare dataset
• Building and evaluating an AI model for medical predictions
• Interpreting model outputs and improving accuracy

Summary and Next Steps