Generative AI in Healthcare

Name: Generative AI in Healthcare
Rating: 4.8 (20 reviews)

Generative AI in Healthcare: Learn Medical AI, Patient Care Automation, Diagnostics, and Real-World Use Cases

Created byYotta Academy

Last updated 5/2026

English

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What you'll learn

Understand how Generative AI is transforming the healthcare industry and its real-world impact.
Learn key concepts of AI, Machine Learning, and Generative AI in a healthcare context.
Explore use cases such as medical report generation, clinical decision support, and patient interaction systems.
Understand how AI models assist in diagnosis, drug discovery, and personalized treatment plans.

Course content

5 sections • 34 lectures • 1h 17m total length

Introduction to Artificial Intelligence and Machine Learning2:34
Key AI Technologies: Deep Learning, Natural Language Processing, Computer Vision2:29
Explore how deep learning, natural language processing, and computer vision drive healthcare's digital transformation, unlocking unstructured text, ambient scribing, and safer care through interoperable EHR systems and human-in-the-loop.
Data Science Fundamentals for Healthcare2:12
AI vs. Traditional Analytics in Healthcare2:15
AI shifts healthcare analytics from descriptive hindsight to foresight by analyzing multimodal data, improving prediction, and enabling proactive care.
Real-World Examples - IBM Watson2:17
Explore how IBM Watson for Oncology aimed to democratize cancer expertise, but data bias and real-world variability limited safety and outcomes, underscoring augmented intelligence with a human in the loop.
AI-powered diagnostic tools in radiology departments2:15
DEMO- Basic machine learning model training using healthcare datasets3:01
Basic Healthcare Prediction Model

AI for Operational Excellence in Healthcare2:43
Leverage AI to achieve operational excellence in healthcare by predicting patient census up to 30 days, optimizing staffing and OR blocks, and enabling just-in-time supply, energy savings, and data-driven decisions.
Predictive Analytics for Patient Flow Management1:22
AI-Powered Staff Scheduling and Resource Optimization2:44
AI-powered scheduling analyzes ER arrivals, acuity, weather, and flu data to forecast demand, reduce premium labor spend, and balance shifts across a 10-hospital system with real-time rebalancing.
Quality Improvement through AI-Driven Insights2:39
Supply Chain Management with AI2:50
Leverage AI to transform hospital supply chains from just-in-time to just-in-case through real-time tracking, forecasting, and autonomous procurement that cut waste and costs.
Cleaveland Clinic2:34
Mayo Clinic's use of AI for predicting patient no-shows2:34
DEMO - Linear model2:36

AI Applications in Healthcare Financial Planning2:05
Harness AI-driven rolling forecasts in real time and activity-based costing to predict cash flow, uncover revenue leakage, and guide proactive, ROI-focused capital investments in healthcare.
Machine Learning for Revenue Cycle Optimization2:25
Fraud Detection and Compliance Monitoring with AI2:18
Cost Analysis and Resource Allocation Using Predictive Models1:40
Leverage ai-driven predictive models to optimize cost analysis and resource allocation in health care, forecasting patient acuity and census to align staffing, supplies, and capital with demand.
AI for Claims Processing and Payer Negotiations1:35
DEMO- Building fraud detection algorithms3:45

Bias, Privacy, and Fairness1:33
Regulatory Landscape: HIPAA, GDPR, FDA Guidelines for AI2:22
Navigate hipaa privacy, gdpr rights to explanation, and fda lifecycle guidelines with change-control plans, cds guidance, model cards, explainability, and bias mitigation across diverse subgroups.
Building AI Governance Frameworks1:19
Change Management for AI Adoption2:16
Ethical challenges faced by facial recognition in hospitals2:54
Explore ethical and legal risks of facial recognition in hospitals, including bias, consent, data security, and mission creep, and learn governance steps like audits, opt-out options, and retention limits.
DEMO- Bed Occupancy3:14
Forecast hospital bed occupancy using day-of-week, month, net admissions, and seven-day rolling averages; train a 300-tree random forest and evaluate with MAE and RMSE.
pratice test

Advanced AI Techniques: Generative AI, Federated Learning2:24
AI in Precision Medicine and Personalized Care2:33
Integration of AI with IoT and Wearables2:13
Integrate AI with the internet of medical things to turn home data from wearables into continuous care, enabling remote monitoring, early intervention, nudges for adherence, and safer, efficient care logistics.
Future of AI in Healthcare: Trends and Predictions2:55
Generative AI in healthcare moves from pilots to enterprise-wide, agentic systems that automate workflows, optimize reimbursement, and support predictive health management with real-time, ambient monitoring.
AI-driven drug discovery at pharmaceutical companies0:30
AI integration with telemedicine platforms during the COVID-19 pandemic0:21
Discover how generative ai integrates with telemedicine platforms to support patient care during the COVID-19 pandemic.
DEMO- Staff Scheduling2:23
Future Trends & Applications

Requirements

1. Basic understanding of computers and the internet
2. No prior experience in AI or healthcare is required
3. Interest in Artificial Intelligence and healthcare innovation
4. Basic knowledge of Machine Learning is helpful but not mandatory

Description

This course contains the use of artificial intelligence.

Generative AI in Healthcare is a comprehensive course designed to help you understand how cutting-edge AI technologies are transforming the medical and healthcare industry.

Generative AI is revolutionizing healthcare by enabling faster diagnoses, improving patient care, and automating complex tasks such as medical documentation and clinical decision-making. In this course, you will explore how AI models are used to generate medical insights, assist healthcare professionals, and enhance operational efficiency.

You will begin with a strong foundation in Artificial Intelligence, Machine Learning, and Generative AI, followed by a deep dive into healthcare-specific applications. The course covers real-world use cases such as AI-powered medical report generation, virtual health assistants, drug discovery, and personalized treatment recommendations.

In addition, you will learn about the ethical challenges and data privacy concerns associated with using AI in healthcare, including responsible AI practices and regulatory considerations.

By the end of this course, you will have a clear understanding and you get of how Generative AI can be applied in healthcare settings and how it is shaping the future of medicine. Whether you are a healthcare professional, student, or tech enthusiast, this course will equip you with valuable insights into one of the most impactful applications of AI.

Who this course is for:

1. Healthcare professionals interested in understanding AI applications
2. Students and beginners curious about AI in the healthcare industry
3. AI enthusiasts looking to explore domain-specific applications

Generative AI in Healthcare

What you'll learn

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Course content

Foundations of AI in Healthcare7 lectures • 17min

AI in Healthcare Management8 lectures • 20min

AI in Healthcare Finance6 lectures • 14min

Ethics, Regulations, and Implementation Strategies6 lectures • 14min

Advanced Applications and Future Trends7 lectures • 13min

Requirements

Description

Who this course is for: