1-Day Conference

AI in Everyday Clinical Practice: Tools for Doctors and Nurses

AMA PRA Category 2 Credit

A practical CME day that introduces medical professionals to artificial intelligence, focusing on how it can improve workflow, support decisions, and safeguard patients.

ai in healthcare

clinical decision support

workflow automation

patient communication

ethics and safety

Destination

Dates

$400

AI in Everyday Clinical Practice: Tools for Doctors and Nurses

About this Conference

This program gives doctors, nurses, and other professionals a clear and accessible overview of AI in healthcare. You will learn what AI can realistically do, how it is being used in clinical practice today, ways it can ease documentation and communication, and what safety and ethical guardrails are needed. The focus is on practical, bedside-relevant insights without unnecessary technical jargon.

7:00 AM - 11:45 AM
Schedule (Local Time): 16 Workshops
Number of Subjects: Online Course
Course Type: New York
Destination

Destination

1-Day Schedule

Conference Outline

Day 1

A practical CME day that introduces medical professionals to artificial intelligence, focusing on how it can improve workflow, support decisions, and safeguard patients.

Section 1

AI 101 for Clinicians: Foundations, Capabilities, and Limits

An accessible introduction to what AI is, how it works in plain language, and what it can and cannot do in clinical settings.

7:00 AM —8:00 AM60 Minutes

Describe in plain terms what AI is and how it differs from traditional computer tools.
Identify realistic examples of AI in healthcare that clinicians may already encounter.
Recognize the common limits and errors AI can make so clinicians can use it safely.

Understanding the Basics of AI

Introduces AI as 'smart computer programs' and explains how they learn patterns from large sets of medical data.

7:00 AM15 Minutes

Define AI in straightforward, practical terms.
Explain how AI systems learn patterns from medical data.
List at least two differences between AI and traditional computer systems.

ai in healthcare

introduction

technology basics

Where AI is Already Helping in Medicine

Shows current examples of AI in radiology, pathology, and patient monitoring that clinicians may already use.

7:15 AM15 Minutes

Identify at least three areas where AI is already in use in clinical practice.
Discuss how AI may improve accuracy in diagnostics.
Recognize how AI fits into existing workflows rather than replacing clinicians.

clinical decision support

diagnostics

imaging

What AI Can and Cannot Do

Explains AI’s strengths, like spotting patterns quickly, and its weaknesses, such as misreading rare cases.

7:30 AM15 Minutes

Explain in plain language what AI systems are best at.
Identify at least two limits of AI in patient care.
Discuss why clinical judgment is always needed with AI tools.

ai in healthcare

safety

clinical practice

Recognizing Errors and Safe Use

Focuses on common mistakes AI tools make and how clinicians can recognize and manage them safely.

7:45 AM15 Minutes

List at least three common types of AI errors.
Describe how to double-check AI suggestions before acting.
Apply at least one safe practice when using AI with patients.

ai in healthcare

clinical safety

error prevention

—

Break

Break time.

8:00 AM15 minutes

Section 2

Clinical AI in Practice: Imaging, Diagnostics, and Risk Tools

Real-world examples of how AI supports diagnosis, image reading, and risk scoring in hospitals and clinics.

8:15 AM —9:15 AM60 Minutes

Identify how AI is used in radiology, cardiology, dermatology, and primary care.
Evaluate the benefits and limitations of AI decision support tools.
Recognize the risks of over-relying on AI in diagnostics.

AI in Radiology and Imaging

Looks at AI tools that help read X-rays, CT scans, and MRIs, and how they compare to radiologist performance.

8:15 AM15 Minutes

Describe how AI supports image interpretation.
List at least two strengths AI brings to imaging.
Discuss how radiologists can use AI as an assistant, not a replacement.

imaging

radiology

clinical decision support

AI in Pathology and Lab Medicine

Explains AI tools that analyze tissue slides and lab data to support faster and more consistent diagnosis.

8:30 AM15 Minutes

Explain how AI is applied to pathology and lab data.
Identify benefits such as improved consistency and speed.
Recognize the need for clinician confirmation of AI results.

pathology

diagnostics

clinical labs

Risk Scores and Prediction Tools

Covers tools that predict sepsis, heart disease, or hospital readmission, and how to use them wisely.

8:45 AM15 Minutes

Describe at least two common risk prediction tools that use AI.
Identify benefits and pitfalls of relying on predictions.
Explain how to combine AI risk scores with patient context.

risk stratification

predictive tools

clinical practice

Avoiding Alert Fatigue and Over-Trust

Discusses risks such as too many alerts or clinicians placing too much trust in AI outputs.

9:00 AM15 Minutes

Explain what alert fatigue is and how AI can contribute.
List at least two strategies to manage AI alerts.
Describe why clinical oversight must remain central.

clinical safety

workflow

decision support

—

Break

Break time.

9:15 AM15 minutes

Section 3

AI Scribes and Workflow Automation

Explores how AI can draft notes, sort messages, prepare orders, and assist in communicating with patients.

9:30 AM —10:30 AM60 Minutes

Describe how AI scribes help with medical note documentation.
Identify ways AI can support communication with patients.
Evaluate safe practices for reviewing and editing AI-generated text.

AI Scribes for Documentation

Introduces AI scribes that listen to patient visits and create draft notes for clinicians to edit.

9:30 AM15 Minutes

Describe how AI scribes record and draft notes.
Identify at least two benefits of AI scribes for clinicians.
Explain why editing and clinician approval are essential.

workflow automation

documentation

patient visits

Sorting Inboxes and Drafting Orders

Explains how AI can help manage message inboxes and suggest orders, saving time for busy clinicians.

9:45 AM15 Minutes

Explain how AI can triage and summarize patient messages.
Describe how AI can suggest basic orders.
Recognize why clinicians must review all AI-generated content.

workflow

clinical orders

automation

Patient-Friendly Communication

Shows how AI can help clinicians write instructions and messages in language patients understand.

10:00 AM15 Minutes

Describe how AI can make medical language easier for patients.
List at least two examples of patient-friendly communication supported by AI.
Explain how to check AI-written messages for accuracy and clarity.

patient communication

education

workflow automation

Reviewing and Editing AI Outputs

Focuses on the importance of clinician review, editing, and responsibility when using AI-drafted materials.

10:15 AM15 Minutes

List at least three risks of using AI-generated text without review.
Explain how to safely edit and finalize AI outputs.
Apply best practices for accountability when using AI tools.

workflow

documentation

clinical safety

—

Break

Break time.

10:30 AM15 minutes

Section 4

Safety, Ethics, and Governance for Clinical AI

Covers safe and ethical use of AI in patient care, focusing on privacy, fairness, and clinician responsibility.

10:45 AM —11:45 AM60 Minutes

Identify key ethical and safety concerns when using AI in healthcare.
Apply strategies to protect patient privacy and confidentiality.
Evaluate how to responsibly explain AI-assisted care to patients.

Bias and Fairness in AI

Explains how AI can sometimes be less accurate for certain groups of patients and how to check for fairness.

10:45 AM15 Minutes

Describe what bias in AI means in plain terms.
Identify at least two examples of how bias can affect patient care.
Explain one way clinicians can watch for unfair results.

ethics

fairness

patient safety

Patient Privacy and Confidentiality

Reviews rules and best practices for protecting patient data when using AI tools.

11:00 AM15 Minutes

Explain why patient privacy is at risk when using AI.
List at least two rules or safeguards for patient data.
Apply at least one practice to keep PHI secure.

privacy

hipaa

data security

Explaining AI-Assisted Care to Patients

Shows how to talk with patients about AI use in their care in straightforward, reassuring language.

11:15 AM15 Minutes

Describe how to explain AI in plain language to patients.
List at least two patient concerns about AI use in care.
Practice at least one reassuring way to frame AI support.

patient communication

ethics

clinical practice

Governance and Professional Responsibility

Focuses on clinician responsibility, professional standards, and oversight for AI use in healthcare.

11:30 AM15 Minutes

Identify key elements of AI oversight in a clinic or hospital.
Describe clinician responsibilities when AI is used in care.
Apply at least one policy or checklist item to guide safe use.

professional standards

ethics

governance

—

End of Day

End of program.

11:45 AM

Key Objectives

Explain the basic concepts of AI in plain terms and describe where it is already used in healthcare.
Evaluate the benefits and risks of AI tools in common clinical settings, including imaging, diagnostics, and documentation.
Apply safe practices for using AI in patient care, including communication, documentation, and ethical considerations.

Virtual Conferences

Flexible Destination-Based Learning

549 Destinations Available

Our conferences are delivered entirely online through short, high-impact video sessions. Designed for travelers and professionals on the go, each module is just 15 minutes—so you can complete your learning in the morning and spend the rest of your day enjoying the destination.

Satisfaction Guaranteed

Reschedule or Cancel Anytime

Easily reschedule or apply your credit to another class—no hassle, no stress. If you prefer a refund, we offer a full return minus a $30 processing fee—because we know you value flexibility.

Frequently asked questions

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How does destination-based learning work?: Destination-based learning is a teaching method that involves students traveling to a specific location to learn about a particular subject. This method allows students to gain a deeper understanding of the subject by experiencing it firsthand.
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Is my travel and lodging included?: Pricing is for the conference itself. Travel and lodging are not included but for some destinations we offer partnership benefits and discounts.
Can I change the destination or scheduled date later?: You can easily change the destination or scheduled date for no fee. You can also request a full refund minus a $30 processing fee.