Artificial Intelligence in Healthcare - A Practical Introduction

Artificial Intelligence in Healthcare - A Practical Introduction


The digital revolution of healthcare is just  starting. At the center of it is artificial intelligence, the technology that will drive innovation in multiple areas of healthcare. In this course we will discuss techniques of AI like computer vision, natural language processing, decision support. We will  discuss clinical and non-clinical applications of these  emerging and maturing AI technologies. Given my background in Neurology we will explore its impact in Neuroscience in Greater Detail.

👥 Who is this course for :

The course is designed to be a bridge between clinicians and engineers.  It is primarily designed for clinicians to understand the impact of artificial intelligence in healthcare. They would be able to effectively communicate with AI engineers and  contribute to the evolving field of artificial intelligence in healthcare.

  • Pre-Meds to understand evolving field of medicine
  • Medical student the chart the future of their career
  • Interns and Resident understand learning Technologies
  • Physician do understand and become advocates for their patients in the emerging field of artificial intelligence in healthcare
  • Computer Engineers trying to bridge Healthcare knowledge with their own computer skills.

🥳 Objectives (By the end of the course …)

By the end of the course clinicians will be able to understand the underlying Technologies of artificial intelligence in healthcare in general and neurosciences in particular. Non clinician will also be able to understand different aspects of AI in Healthcare and it applications to work with clinicians in improving outcomes of our patients

Table of Contents

6.1 - Intro & Goal

Not to make you experts in AI in Healthcare

This is for your understand the importance of AI in Healthcare

The Idea is to understand how it will change healthcare

How it impacts your choice of Specialty

6.1.1 - What Leaders are Saying

Artificial intelligence has the potential to radically change health care. AI and Healthcare Are Made for Each Other - Geralyn Miller - Senior Director, AI for Good Research Lab at Microsoft

Artificial intelligence represents one of technology's most important priorities, and healthcare is perhaps AI's most urgent application - Satya Nadella - CEO Microsoft

AI is the new electricity. Just as 100 years ago electricity transformed industry after industry, AI will now do the same. - Andrew Ng - Founder of DeepLearning.AI

Artificial Intelligence Is One Of The Most Profound Things Humanity Is Working On, More Profound Than Fire Or Electricity. - Google CEO Sundar Pichai

Will AI ever replace radiologists? “I say the answer is no—but radiologists who use AI will replace radiologists who don’t.” - Curtis Langlotz, MD, PhD

6.1.2 - Number of Peer-Reviewed AI Publication

👈 [Toggle] 6.1.2 - Number of Peer-Reviewed AI Publication

6.1.3 - Understanding Hype vs Impact

👈 [Toggle] 6.1.3 - Understanding Hype vs Impact

We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run. - Roy Amara - Senior Director, AI for Good Research Lab at Microsoft

“In Silicon Valley, they always say you overestimate what can be done in a year, but you underestimate what can be done in ten years.” - Hal Varian, the Chief Economist at Google


6.1.4 - Augmented, Assistive, Applied, Ambient, Autonomous

👈 [Toggle] 6.1.4 - 5As of Intelligence

Augment, Assist, Apply, Ambient, Autonomous - 5 As of AI

Humans are at the heart of AI not the other way around.

It can assist and augment diagnostics, automate logistics & minutiae in healthcare.

Contextually provide applicable relevant information

So I can concentrate on my patient and not the computer.

AI can make medicine more human again.

Goal “Not to replace providers - may be just a few physicians”

Goals of ML in healthcare:

  • Augment physicians' by Computer aided DDD
    • DDD: Detection, Diagnosis and Decision
  • Augment physicians' efficiency CCC
    • CCC: Compare, Context and Communicate

Example of AI applications across the human lifespan


Example of AI applications across the human lifespan

Virtual Wellness Coach Powered by AI


The Virtual health coach - Future of healthcare powered by AI

Comparing Autonomy: Healthcare vs Autonomous Vehicle


Analogy between Self-driving cars & Medicine

6.1.5 - Human vs AI Intelligence

👈 [Toggle] 6.1.5 - Human vs AI Intelligence

6.1.5 - Human vs AI Intelligence

No Recall Bias
Mimic Language (NLP)

  • Early AI came with a subhuman performance and varying degrees of success.
  • Currently, we are witnessing narrow task-specific AI applications that are able to match and occasionally surpass human intelligence–,.
  • It is expected that general AI will surpass human performance in specific applications within the coming years.
  • Humans will potentially benefit from the human-AI interaction, bringing them to higher levels of intelligence.

Computers will never be as good as Human "eye”

You are missing the point


Human eye is limited to the visible spectrum. On the contrary Computer vision is NOT!


6.1.6 - Recent Examples & Investments

👈 [Toggle] 6.1.6 - Recent Examples & Investments

Your AI pair programmer

GitHub Copilot, get suggestions for whole lines or entire functions right inside your editor

GitHub Copilot is powered by Codex, the new AI system created by OpenAI [GPT-3]

GitHub Copilot understands significantly more context than most code assistants


One company, Blue Dot, used NLP and ML to detect the COVID-19 virus before the US Center for Disease Control

BlueDot was among the first in the world to identify the emerging risk from COVID-19 in Hubei province and notify our clients via our Insights platform

BlueDot published the first scientific paper on COVID-19, accurately predicting eight of the first ten cities to import the novel coronavirus.

Halicin was the first antibiotic discovered using AI

Artificial intelligence yields new antibiotic

The AI found molecules that even help treat formerly untreatable bacterial strains

A deep-learning model identifies a powerful new drug that can kill many species of antibiotic-resistant bacteria

Google to use patient data to develop healthcare algorithms for hospital chain

“We want to push the boundaries of what the clinician can do in real-time with data,”

Chris Sakalosky, managing director of healthcare and life sciences at Google Cloud

6.2 - Why Now?

6.2 - Why Now?

6.3 - Technical Basics of AI in Healthcare

6.3 - Technical Basics of AI in Healthcare

6.4 - Challenges and Limitations

6.4 - Challenges, Limitations & Ethics in AI

6.5 - Specialties Most Impacted by AI

Specialties Most Impacted by AI

6.6 - Resources & Reads

6.6 - Resources & Reads