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AP 5010
AI+ Medical Assistant Practitioner™
Formerly known as AI+ Medical Assistant™
Revolutionize Healthcare Support with AI-Powered Medical Assistance
Revolutionize Healthcare Support with AI-Powered Medical Assistance
AI HealthcareAI Professional
Enquire about this certificationAt a glance
What is included
Instructor-led OR Self-paced course + Official exam + Digital badge
Duration
- Instructor-Led: 1 day (live or virtual)
- Self-Paced: 8 hours of content
Recommended background
A basic understanding of medical terminology, foundational AI and machine-learning concepts, data analytics skills for interpreting medical data, proficiency in programming languages like Python, and knowledge of healthcare systems and clinical workflows are essential for this course.
Examination
50 questions, 70% passing, 90 minutes, online proctored exam
About this certification
- 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.
Curriculum
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
Who should enrol
Healthcare Support Professionals: Individuals looking to enhance their skills with AI tools to streamline patient care and improve clinical support.
Medical Office Administrators: Professionals interested in using AI to automate administrative tasks, optimize scheduling, and enhance patient coordination.
Clinical Staff Members: Nurses, medical assistants, and technicians aiming to integrate AI into their daily workflows for improved efficiency and patient care.
Aspiring Medical Technologists: Those seeking to work with AI-driven medical tools and enhance diagnostic capabilities and patient monitoring.
Healthcare Technology Enthusiasts: Individuals passionate about merging healthcare knowledge with AI innovations to drive digital transformation in medical settings.
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