AI in Healthcare: Insights for Users, Buyers, and Investors

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AI in Healthcare: Insights for Users, Buyers, and Investors

Instructor: Wiley-Expert Edge Course Instructors

14 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

14 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Explore how AI is transforming clinical practices and patient care
Understand the challenges and barriers to AI adoption in healthcare
Discover how AI enhances diagnostics and therapeutic applications

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There are 14 modules in this course

Based on the book, AI Doctor, by Ronald M. Razmi. This course explores how artificial intelligence is revolutionizing healthcare, from enhancing diagnostics to improving patient care. It provides practical insights into AI's role in operational efficiency, healthcare economics, and business models.

Through a non-technical approach, learners will gain a comprehensive understanding of AI’s potential to reshape healthcare systems. The course will cover both the benefits and challenges of implementing AI in various healthcare sectors. What makes this course unique is its blend of theory with real-world applications. It provides a strategic overview of AI's impact on healthcare, focusing on practical examples and case studies. Ideal for healthcare professionals, researchers, business leaders, and investors, the course is also suitable for medical students and tech enthusiasts looking to explore AI’s transformative role in healthcare. No prior technical expertise is required. Copyright © 2024 by Ronald M. Razmi. Published by John Wiley & Sons, Inc., Hoboken, New Jersey.

In this section, we explore the evolution of AI from the 1940s to modern times, focusing on neural networks, their limitations, and applications in healthcare.

What's included

2 videos5 readings1 assignment

2 videosTotal 2 minutes

Course Overview1 minute
History of AI and Its Promise in Healthcare - Overview Video1 minute

5 readingsTotal 60 minutes

Introduction10 minutes
What is AI?20 minutes
A Classification System for Underlying AI/ML Algorithms10 minutes
AI and Deep Learning in Medicine10 minutes
The Emergence of Multimodal and Multipurpose Models in Healthcare10 minutes

1 assignmentTotal 10 minutes

Evolution and Capabilities of AI in Medical Contexts10 minutes

In this section, we examine the challenges of healthcare data quality, standardization, and security, emphasizing their impact on medical AI reliability and performance.

What's included

1 video10 readings1 assignment

1 videoTotal 1 minute

Building Robust Medical Algorithms - Overview Video1 minute

10 readingsTotal 140 minutes

Introduction10 minutes
Obtaining Datasets That Are Big Enough and Detailed Enough for Training10 minutes
Data Access Laws and Regulatory Issues10 minutes
Federated AI as a Possible Solution30 minutes
Synthetic Data10 minutes
Data Labeling and Transparency10 minutes
Model Explainability20 minutes
Model Performance in the Real World10 minutes
Training on Local Data20 minutes
Responsible AI10 minutes

1 assignmentTotal 10 minutes

Building Reliable Medical AI Systems10 minutes

In this section, we examine barriers to AI adoption in healthcare, including cost, talent shortages, trust issues, and regulatory challenges. Key concepts focus on practical solutions for overcoming these obstacles.

What's included

7 readings1 assignment

In this section, we examine how data availability, computing power, and healthcare resource shortages drive AI adoption. Key concepts include policy impacts, cost efficiency, and precision medicine applications.

What's included

1 video5 readings1 assignment

In this section, we examine AI's role in healthcare diagnostics and data interpretation.

What's included

1 video12 readings1 assignment

1 videoTotal 1 minute

Diagnostics - Overview Video1 minute

12 readingsTotal 135 minutes

Introduction20 minutes
Pathology10 minutes
Dermatology5 minutes
Ophthalmology10 minutes
Cardiology20 minutes
Neurology10 minutes
Oncology10 minutes
Prognosis Detection10 minutes
Genomics10 minutes
Diagnostic Bots10 minutes
At Home Diagnostics/Remote Monitoring10 minutes
Sound AI10 minutes

1 assignmentTotal 10 minutes

AI in Modern Diagnostic Practices10 minutes

In this section, we examine digital therapeutics in mental health, chronic disease, and market growth.

What's included

1 video4 readings1 assignment

In this section, we explore AI-driven decision support, challenges in data integration, and the importance of structured formats.

What's included

1 video6 readings1 assignment

In this section, we explore AI-driven personalization in health and wellness, focusing on real-time data analysis from wearables and predictive modeling for scalable, individualized health solutions.

What's included

1 video7 readings1 assignment

1 videoTotal 1 minute

Population Health and Wellness - Overview Video1 minute

7 readingsTotal 110 minutes

Introduction20 minutes
Fitness20 minutes
Population Health and Management30 minutes
Risk Assessment10 minutes
Remote Engagement and Automation10 minutes
SDOH10 minutes
Aging in Place10 minutes

1 assignmentTotal 10 minutes

Population Health and Wellness Technologies10 minutes

In this section, we explore AI's role in clinical workflows, reducing burnout, and improving efficiency through automation.

What's included

1 video4 readings1 assignment

In this section, we examine administrative inefficiencies in healthcare, focusing on costs, insurance complexity, and AI's role in streamlining workflows and reducing expenses.

What's included

1 video5 readings1 assignment

In this section, we explore AI's role in analyzing genomics and clinical data, improving drug discovery, and creating structured databases for life sciences applications.

What's included

1 video5 readings1 assignment

In this section, we examine the readiness of AI applications in healthcare, focusing on NLP for clinical decision support, deep learning for stroke detection, and LLMs for point-of-care use. The discussion highlights the alignment of technical maturity with clinical relevance.

What's included

1 video4 readings1 assignment

In this section, we examine AI use cases in healthcare to identify those with measurable ROI, focusing on clinical, administrative, and life science applications that improve efficiency and outcomes.

What's included

1 video4 readings1 assignment

In this section, we explore identifying viable AI business models in healthcare, analyzing stakeholder roles, and evaluating ROI for life science applications.

What's included

1 video7 readings1 assignment

1 videoTotal 1 minute

How to Build and Invest in the Best Health AI Companies - Overview Video1 minute

7 readingsTotal 45 minutes

Introduction5 minutes
Barriers to Entry and Intellectual Property (IP)5 minutes
Creating Defensible Products5 minutes
Startups Versus Large Companies5 minutes
Sales and Marketing10 minutes
Initial Customers5 minutes
Direct-to-Consumer (D2C)10 minutes

1 assignmentTotal 10 minutes

Health AI Investment and Development Insights10 minutes

Instructor

Wiley-Expert Edge Course Instructors

John Wiley & Sons

33 Courses1,275 learners

Offered by

John Wiley & Sons

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