BONUS! Cyber Phoenix Subscription Included: All Phoenix TS students receive complimentary ninety (90) day access to the Cyber Phoenix learning platform, which hosts hundreds of expert asynchronous training courses in Cybersecurity, IT, Soft Skills, and Management and more!
Course Overview
Phoenix TS 1-day, instructor-led AI+ Doctor training and certification course in Washington, DC Metro, Columbia, MD, or Live Online introduces medical professionals to the practical use of artificial intelligence in clinical practice and patient care. Participants will explore AI technologies that support diagnostics, predictive analytics, and patient monitoring. The course emphasizes how AI can improve decision-making, treatment outcomes, and overall healthcare efficiency, bridging medical expertise with emerging digital tools.
As an AI CERTs Silver Tier Partner, Phoenix TS delivers official AI CERTs certification programs and offers self-paced learning options at competitive pricing, making it easier than ever for individuals and teams to stay ahead in today’s AI-driven workplace.
Schedule
Currently, there are no public classes scheduled. Please contact a Phoenix TS Training Consultant to discuss hosting a private class at 301-258-8200.
Why AI Doctor™ Matters?
- Clinical Intelligence Focus: Designed for medical professionals to integrate AI into patient care and diagnostics
- Data-Driven Decisions: Equips doctors with tools to interpret AI-generated insights for precise treatment planning
- Comprehensive Medical AI Knowledge: Covers AI applications from predictive analytics to medical imaging and virtual health
- Future-Ready Expertise: Empowers healthcare practitioners to lead AI-driven innovations in clinical practice
Exam Overview
Program Name: AI+ Doctor™
Duration: Instructor-Led: 1 day (live or virtual)
Prerequisites:
- Basic Medical Knowledge
- Familiarity with Healthcare Systems
- Interest in Technology Integration
- Data Literacy
- Problem – Solving Mindset
Exam Format: 50 questions, 70% passing, 90 minutes, online proctored exam
Delivery: Projects & case studies
Outcome: Industry-recognized credential + hands-on experience
What You’ll Learn
- Gain an understanding of AI applications in modern medicine and healthcare delivery.
- Explore AI tools for diagnostics, predictive analytics, and patient monitoring.
- Learn how AI-driven insights can enhance clinical decision-making and workflows.
- Consider ethical, legal, and regulatory issues in the use of AI in healthcare.
- Identify ways to integrate AI solutions to improve patient care and operational efficiency.
Who Should Enroll?
- Healthcare Professionals
Skills You Gain
- AI in medicine and diagnostics
- Machine learning & neural networks
- Medical imaging analysis
- Clinical data analysis
- Predictive analytics
- NLP & generative AI
- Ethical & unbiased AI use
- AI tool evaluation
- AI implementation & workflow integration
Course Outline
What is AI for Doctors?
- From Decision Support to Diagnostic Intelligence
- What Makes AI in Medicine Unique?
- Types of Machine Learning in Medicine
- Common Algorithms and What They Do in Healthcare
- Real-World Use Cases Across Medical Specialties
- Debunking Myths About AI in Healthcare
- Real Tools in Use by Clinicians Today
- Hands-on: Medical Imaging Analysis using MediScan AI
AI in Diagnostics Imaging
- Introduction to Neural Networks: Unlocking the Power of AI
- Convolutional Neural Networks (CNNs) for Visual Data: Seeing with AI’s Eyes
- Image Modalities in Medical AI: AI’s Multi-Modal Vision
- Model Training Workflow: From Data Labeling to Deployment – The AI Lifecycle in Medicine
- Human-AI Collaboration in Diagnosis: The Power of Augmented Intelligence
- FDA-Approved AI Tools in Diagnostic Imaging: Trust and Validation
- Hands-on Activity: Exploring AI-Powered Differential Diagnosis with Symptoma
Introduction to Fundamental Data Analysis
- Understanding Clinical Data Types – EHRs, Vitals, Lab Results
- Structured vs. Unstructured Data in Medicine
- Role of Dashboards and Visualization in Clinical Decisions
- Pattern Recognition and Signal Detection in Patient Data
- Identifying At-Risk Patients via Trends and AI Scores
- Interactive Activity: AI Assistant for Clinical Note Insights
Predictive Analytics Clinical Decision Support Empowering Proactive Patient Care
- Predictive Models for Risk Stratification – Sepsis and Hospital Readmissions
- Logistic Regression, Decision Trees, Ensemble Models
- Real-Time Alerts – Early Warning Systems (MEWS, NEWS)
- Sensitivity vs. Specificity – Metric Choice by Clinical Need
- ICU and ER Use Cases for AI-Triggered Interventions
NLP and Generative AI in Clinical Use
- Foundations of NLP in Healthcare
- Large Language Models (LLMs) in Medicine
- Prompt Engineering in Clinical Contexts
- Generative AI Use Cases – Summarization, Counselling Scripts, Translation
- Ambient Intelligence: Next-Gen Clinical Documentation
- Limitations & Risks of NLP and Generative AI in Medicine
- Case Study: Transforming Clinical Documentation and Enhancing Patient Care with Nabla Copilot
Ethical and Equitable AI Use
- Algorithmic Bias – Race, Gender, Socioeconomic Impact
- Explainability and Transparency (SHAP and LIME)
- Validating AI Across Populations
- Regulatory Standards – HIPAA, GDPR, FDA/EMA Compliance
- Drafting Ethical AI Use Policies
- Case Study – Biased Pulse Oximetry Detection
Evaluating AI Tools in Practice
- Core Metrics: Understanding the Basics
- Confusion Matrix & ROC Curve Interpretation
- Metric Matching by Clinical Context
- Interpreting AI Outputs: Enhancing Clinical Decision-Making
- Critical Evaluation of Vendor Claims: Ensuring Reliability and Effectiveness
- Red Flags in Commercial AI Tools: Recognizing and Mitigating Risks
- Checklist: “10 Questions to Ask Before Buying AI Tools”
Implementing AI in Clinical Settings
- Identifying Department-Specific AI Use Cases
- Mapping AI to Workflows (Pre-diagnosis, Treatment, Follow-up)
- Pilot Planning: Timeline, Data, Feedback Cycles
- Team Roles – Clinical Champion, AI Specialist, IT Admin
- Monitoring AI Errors – Root Cause Analysis
- Change Management in Clinical Teams
- Example: ER Workflow with Triage AI Integration
- Scaling AI Solutions Across the Healthcare System
- Evaluating AI Impact and Performance Post-Deployment
Frequently Asked Questions
Can I apply what I learn in this course to real-world scenarios immediately?
- Yes, this certification equips you with practical skills through real clinical scenarios and hands-on projects. You’ll be ready to apply AI tools directly in healthcare settings.
What makes this course different from other Healthcare and AI courses?
- This certification combines clinical context with hands-on AI training, focusing on real-world applications in diagnostics and patient care.
What type of projects will I work on?
- You’ll work on AI diagnostics, image analysis, EHR mining, and predictive models—simulating real clinical challenges for job-ready skills.
How is the course structured to ensure I actually learn the skills?
- This course blends expert lessons, interactive modules, and hands-on projects with real clinical case studies. This ensures practical learning and strong skill retention.
How does this course prepare me for the job market?
- It equips you with in-demand AI skills, real-world healthcare projects, and domain knowledge aligned with current industry job roles.
BONUS! Cyber Phoenix Subscription Included: All Phoenix TS students receive complimentary ninety (90) day access to the Cyber Phoenix learning platform, which hosts hundreds of expert asynchronous training courses in Cybersecurity, IT, Soft Skills, and Management and more!
Phoenix TS is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have final authority on the acceptance of individual courses for CPE credit. Complaints re-garding registered sponsors may be submitted to the National Registry of CPE Sponsors through its web site: www.nasbaregistry.org
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