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Slide 1Slide 2Slide 3Slide 4Slide 5Slide 6Slide 7Slide 8Slide 9Slide 10Slide 11Slide 12Slide 13Slide 14Slide 15Slide 16Slide 17Slide 18Slide 19
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2026-08-23T02:20:33Z
2026-08-23T02:20:33Z
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AI IN DAILY MEDICAL PRACTICEModule 1AI Foundations for Clinical PracticeSelf-paced · ~2.5 hrs totalAI in Daily Medical Practice — a curriculum for practicing physiciansPK
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BEFORE YOU STARTHow this self-paced module works1Preview Quiz5 min, ungraded. Orients you before reading.→2Handout / SlidesTwo formats, same content. Use either.→3Post-Test12 questions, scored. 80% pass, retake anytime.→4Module 2Opens once Module 1 is evaluated.2PK
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BY THE END OF THIS MODULEYou will be able to1Explain in plain clinical terms how generative AI and clinical AI tools work — including their core failure modes.2Distinguish appropriate from inappropriate clinical use cases for a given AI tool.3Identify which AI tools are realistically accessible and affordable in your own practice setting.3PK
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WHY THIS MODULE STARTS HEREAugmentation, not outsourcingThe technology is identical in both cases below. The outcome is not.COGNITIVE OUTSOURCINGAsk AI for a differential diagnosis. Copy it into the chart. No second thought.The thinking has been handed over — not assisted.COGNITIVE AUGMENTATIONAsk AI for a differential. Then interrogate it — what's missing, why ranked first, does it fit this patient.The tool extended your reasoning — it didn't replace it.4PK
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THE WORKING RULE FOR THIS ENTIRE COURSEUse AI to extend your thinking.Never let it replace your thinking.5PK
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THE MODEL BEHIND THIS COURSEKNOW · FIND · THINKKNOWWhat must be in your head, unaided — for real-time decisions with no time to look anything up.FINDWhat you should know exists, and know how to retrieve when you actually need it.THINKWhat you do with the first two layers — judging fit for a real patient, a real clinic.6PK
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ASECTION AWhat AI Actually IsKNOW7PK
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SECTION A · CORE VOCABULARYNine terms cover what you need (1/3)Artificial intelligence (AI)Software performing tasks that normally require human judgment — a category, not one technology.Machine learning (ML)The dominant technique: systems learn statistical patterns from large amounts of example data, rather than fixed rules.Large language model (LLM)Trained on huge amounts of text; predicts plausible next words. Powers most AI scribes and chat-style tools.8PK
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SECTION A · CORE VOCABULARY...continued (2/3)Generative AIAny AI that produces new content — text, images, draft notes — rather than only classifying input.Multimodal AIWorks across more than one input type — e.g. reading a note and an image in the same session.Training dataThe examples a system learned from. A tool is only as good as the population it was trained on.9PK
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SECTION A · CORE VOCABULARY...continued (3/3)PromptThe instruction you give the tool. Vague prompts → vague answers; specific, contextual prompts → useful ones.InferenceThe tool actually doing the task for your input — as opposed to the training phase that already happened.HallucinationFluent, confident, but factually wrong or fabricated output. The most important failure mode in this course.10PK
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BSECTION BHow These Systems FailKNOW11PK
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SECTION B · READ THIS ONE CAREFULLYHallucinationAn LLM predicts plausible next words — it has no built-in signal that distinguishes “I am certain” from “I am guessing.” Both come out sounding equally confident.WHAT THIS LOOKS LIKE IN PRACTICEAn AI drafting a discharge letter references a lab result that was never in the chart — phrased with the exact same fluency and confidence as every accurate line around it. Nothing in the tone signals that this line is fabricated.12PK
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SECTION B · TWO MORE FAILURE MODESOverconfidence & biasOverconfidenceAI rarely hedges the way a cautious colleague would. It often generates one confident answer even when the evidence is thin or conflicting.The danger isn't that the tool is sometimes wrong — every aid is. It's that wrong answers look identical to right ones.BiasThese systems inherit whatever imbalances exist in their training data — different demographics, disease prevalence, presentation patterns.“The tool works well” depends entirely on whom it was validated against — never automatically true for your patients.13PK
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THE TRAP THAT MATTERS MOST FOR YOU PERSONALLYEvery failure mode becomes most dangerousat exactly one moment:when the AI's answer matches what you already suspectedThat's when scrutiny drops — because it feels like confirmation, not a claim that needs checking. Module 4 is built entirely around training vigilance at this exact moment.14PK
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CSECTION CThe Clinical AI Landscape TodayFIND15PK
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SECTION C · FOUR CATEGORIES COVER ALMOST EVERYTHINGWhich of these four is it?1Ambient documentation / scribingDrafts a structured note from a listened or transcribed encounter.→ Module 22Diagnostic / decision supportSuggests differentials, flags abnormal imaging or labs, estimates risk.→ Module 33Patient-facing toolsSymptom checkers and chatbots patients use themselves and bring in.→ Module 34Administrative / operationalScheduling, billing support, referral triage, supply chain.→ Module 616PK
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SECTION D · THINKWhat Actually Fits Your PracticeA self-directed worksheet in the handout — no live seminar. Work through five questions on your own; you'll return to your answers in Module 6.1Which tool category is most relevant to your day-to-day work right now — and why that one first?2What is your actual connectivity like — does the tool need to tolerate offline or low-bandwidth use?3What languages do your encounters happen in — and does the tool handle them well?4What would this tool realistically cost against what your practice can sustain?5Where was this tool validated — does that population resemble your patients?17PK
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BEFORE YOU MOVE ONModule 1 summaryKNOWNine core terms, plus three failure modes — hallucination, overconfidence, bias — with confirmation bias flagged as most personally dangerous.FINDFour categories of clinical AI tools, and where to look for current product-specific detail when you need it.THINKA first pass at judging tool fit for your practice — connectivity, language, cost, validation population.18PK
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NEXT STEPSTake the Post-Test12 scored questions, 80% pass mark. Once Module 1 is evaluated, Module 2 — AI for Clinical Documentation & Administrative Efficiency — opens next.Module 1 of 6 — AI Foundations for Clinical Practice19PK
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7/23/19Click to edit Master text stylesSecond levelThird levelFourth levelFifth level‹#›PK
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