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

Access to all materials and exams is provided for 365 days after delivery.

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