Objectives
- Define the major types of artificial intelligence relevant to healthcare
- Describe current and emerging applications of AI in rheumatology
- Evaluate the limitations, ethical concerns, and future directions of AI integration in rheumatologic practice
AI Basics
- Definitions & hierarchy: Algorithms → Machine Learning → Deep Learning → Transformers → Large Language Models (LLMs)
- Transformers introduced self-attention (Vaswani et al. 2017)
- Pretraining concepts: tokenization (OpenAI Tokenizer), embeddings, Q/K/V attention, multi-head attention, transformer blocks (Interactive explainer)
- Role of GPUs in AI training, FLOPS, and NVIDIA’s dominance
Evolution of Models
- GPT-3 (2020): 175B parameters, first to capture public attention
- GPT-3.5 (2022): Refinements, powered first ChatGPT release
- GPT-4 (2023): 1–1.8T parameters, major leap in reasoning, high exam scores
- GPT-4o (2024): Multimodal, real-time capabilities
- GPT-o3 (2024): Optimized for reasoning efficiency
- GPT-5 (2025): >10T parameters (est.), frontier model, improved efficiency
Leaderboards and benchmarks:
Artificial General Intelligence (AGI)
- No clear definition; can it perform any intellectual task a human can do?
- Apple’s perspective: The Illusion of Thinking
Using General AI Tools
- Different “personalities” across ChatGPT, Grok, Claude, Gemini
- Prompt engineering: role → task → context → format → extras
Current Uses in Medicine
- Clinical documentation: ambient scribes (Heidi Health, Nuance DAX, Abridge, Suki, DeepScribe, Augmedix)
- Decision support: OpenEvidence, Vera Health, UpToDate AI
- Imaging: Google Health AI Foundations
- Pathology: PathAI
- Physical exam: AI detection of Parkinson’s via smile videos (NEJM AI 2025)
- Genomics: AlphaFold Protein Structure Database
- Regenerative medicine: OpenAI + Retro Biosciences redesigned Yamanaka factors with AI (OpenAI announcement)
AI Agents
- Chatbots answer single questions
- Agents execute multi-step workflows with oversight
- Non-healthcare agents: email, browser, coding (Cursor), productivity (Microsoft Copilot, Google Gemini apps)
- Spreadsheet integrations: Google Sheets
=AI(...), Excel=COPILOT(...) - EHR agents: Epic, Oracle Health
Risks & Limitations
- Errors & hallucinations: confident but wrong answers, fabricated references
- Liability: unclear responsibility, evolving regulatory standards
- Ethics: bias, transparency, patient trust
- Why models hallucinate: OpenAI report
Future Directions
- Deeper integration into everyday tech and EHRs
- Agentic workflows
- Multimodal healthcare inputs (history, labs, imaging, pathology, genomics)
- Regulatory evolution
- Workforce impact: efficiency ↑, burnout ↓
Practical Tips
- Create 2+ AI accounts (ChatGPT, Gemini, Claude, Grok)
- Try an ambient scribe
- Test decision tools (OpenEvidence, Vera Health)
- Practice structured prompting
- Use AI to summarize journal articles
Thanks to everyone who attended!