AI+ Medical Assistant™ eLearning

Revolutionize Healthcare Support with AI-Powered Medical Assistance

• Patient Interaction Excellence: Learn how AI enhances patient communication, appointment scheduling, and follow-up care to improve the patient experience.
• Clinical Workflow Efficiency: Master AI tools for streamlining patient intake, medical record management, and lab result analysis to optimize clinical operations.
• Data-Driven Decision Support: Gain expertise in using AI to assist healthcare providers with accurate diagnostics, treatment suggestions, and patient monitoring.
• Enhanced Medical Administration: Prepare to support healthcare teams with AI-driven administrative tasks, reducing errors, improving accuracy, and enabling faster decision-making.

Module 1: Fundamentals of AI for Medical Assistants

• 1.1 Understanding AI and Its Healthcare Applications
• 1.2 The Role of AI in Medical Assistance
• 1.3 Case Studies
• 1.4 Hands-on Session: Functionality Survey and Stepwise Analysis of the Eka.care Patient-Side Application

Module 2: Data Literacy for Medical Assistants

• 2.1 Healthcare Data Types and Management
• 2.2 Using Data Effectively in AI
• 2.3 Case Studies
• 2.4 Hands-On Session: Structured vs. Unstructured Data in Healthcare: A Practical Study Using Eka.Care Patient Health Record System

Module 3: AI in Patient Care Optimization

• 3.1 Enhancing Patient Interactions with AI
• 3.2 Predictive Analytics and Workflow Management
• 3.3 Case Studies
• 3.4 Hands-On Session: Eka.care in Action: Appointment Management, Smart Reminders & Tele-Consult Dashboards

Module 4: NLP and Generative AI in Medical Documentation

• 4.1 Foundations of NLP for Medical Assistants
• 4.2 Practical Applications and Risks
• 4.3 Case Studies
• 4.4 Hands-On Simulation Exercise
• 4.5 Hands-On Session: Automating Clinical Documentation Using Eka.care: Notes, Summaries, and Communication Workflows

Module 5: AI in Diagnostics and Screening

• 5.1 Diagnostic Support Tools
• 5.2 Real-World Applications and Simulation
• 5.3 Use Cases
• 5.4 Hands-On: AI-Powered Detection of Common Health Conditions: Review and Analysis of AI-Suggested Diagnostic Insights using Eka Care

Module 6: Ethics, Bias, and Regulation in AI for Healthcare

• 6.1 Recognizing and Addressing Bias in AI
• 6.2 Legal, Ethical, and Compliance Frameworks
• 6.3 Hands-On Exercise: Analyzing and Visualizing Bias in Artificial Intelligence Systems — Exploring Racial, Socioeconomic, and Demographic Disparities using Google’s What-If Tool

Module 7: Evaluating and Implementing AI Tools

• 7.1 Selecting and Planning for AI Adoption
• 7.2 Best Practices and Stakeholder Engagement
• 7.3 Case Study: Procurement and Early Deployment of AI Tools for Chest Diagnostics in a National Health Service Setting
• 7.4 Hands-On Simulation Exercise: Recognizing Red Flags in Vendor Solutions for AI in Medical Assistant
• 7.5 Hands-On Exercises: Evaluating the Relevance and Effectiveness of AI Models using the Zoho Analytics

Module 8: Cybersecurity and Emerging Trends in AI

• 8.1 Cybersecurity Risks and Protection
• 8.2 Future Trends and Preparing for Innovation
• 8.3 Case Studies: EY’s Strategic Transformation: Adapting to Emerging AI Technologies
• 8.4 Hands-On Exercises: Common Cybersecurity Threats in AI-Enabled Healthcare: A Hands-On Exploration Using Google Sheets

Tools you will explore

• TensorFlow
• Keras
• Python
• Natural Language Processing (NLP) Tools
• SQL
• Matplotlib
• Power BI
• Healthcare Data Integration Tools
• Electronic Health Record (EHR) Systems
• Patient Scheduling and Coordination Platforms
• AI-Powered Diagnostic Tools
• Medical Imaging Analysis Tools

Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam

Self study materials are available for 365 days.

Instructor-led OR Self-paced course + Official exam + Digital badge