Course Overview:
Artificial intelligence (AI) has transformed industries around the world and has the potential to radically alter the field of healthcare. Imagine being able to analyze data on patient visits to the clinic, medications prescribed, lab tests, and procedures performed, as well as data outside the health system — such as social media, purchases made using credit cards, census records, Internet search activity logs that contain valuable health information, and you’ll get a sense of how AI could transform patient care and diagnoses.
In this mini course, we’ll discuss the current and future applications of AI in healthcare with the goal of learning to bring AI technologies into the clinic safely and ethically.
This course is designed for healthcare providers to be able to cooperate with computer science professionals, offering insights to facilitate collaboration between the disciplines towards bringing AI technology into healthcare institutions.
Course Content:
- Day 1: Introduction to Healthcare systems and their challenges
In our first day we explore the fundamentals of healthcare systems. We introduce the principal institutions and participants in healthcare systems, explain what they do, and discuss the interactions between them. We will cover physician practices, hospitals, pharmaceuticals, and insurance and financing arrangements. We will also discuss the challenges of healthcare cost management, quality of care, and access to care.
- Day 2: Clinical Data to the Rescue
This part brings data to the healthcare scene and introduces a framework for successful and ethical medical data mining. We will explore the variety of clinical data collected during the delivery of healthcare. We will learn to construct analysis-ready datasets and apply computational procedures to answer clinical questions. We will also explore issues of fairness and bias that may arise when we leverage healthcare data to make decisions about patient care.
- Days 3 and 4: Machine Learning for Healthcare
Machine learning and artificial intelligence hold the potential to transform healthcare and open up a world of incredible promise. But we will never realize the potential of these technologies unless all stakeholders have basic competencies in both healthcare and machine learning concepts and principles.
During days 3 and 4, we will introduce the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. We will explore machine learning approaches, medical use cases, metrics unique to healthcare, as well as best practices for designing, building, and evaluating machine learning applications in healthcare. This will be a very high-level introduction to the machine learning fundamentals tailored to medical students and focusing on healthcare problems.
- Day 5: Evaluations of AI Applications in Healthcare
With artificial intelligence applications proliferating throughout the healthcare system, stakeholders are faced with both opportunities and challenges of these evolving technologies. This part explores the principles of AI deployment in healthcare and the framework used to evaluate downstream effects of AI healthcare solutions. The main goal at the end of the week is to give our medical students the opportunity to think of possible AI solutions to real healthcare problems and be able to evaluate the effect of deploying them with quantifiable measures.
Course Assessment:
A research assignment (group or individual) should be submitted at the end of the course. The student(s) should find a healthcare problem and show possible solution(s) using AI applying the concepts learned during the course. We could also give them a couple of mini formative assignments throughout the week to help them.
Intended Learning Outcomes (ILOS):
A student who successfully completes this mini course will have the ability to:
1. Analyze challenges and risks facing modern healthcare systems.
2. Bring data ethically and efficiently to the healthcare scene to answer questions and solve challenges facing modern healthcare.
3. Appreciate the potential of AI and Machine learning to harness the power of clinical data towards better healthcare systems.
4. Discuss and cooperate with information technology professionals to bring AI into the healthcare scene.
Certificate:
Certificates will be granted to participants based on full course attendance.
For inquiries and corporate deals, please send us an email on pda@ngu.edu.eg