Quiz połączony z przewodnikiem · Ciężko Poziom
Używanie ChatGPT do quizu diagnostyki różnicowej
Sprawdza, co wykazały badania Kanjee i Goh na temat diagnostyki GPT-4, dlaczego testy porównawcze winiet zawyżają dokładność przy łóżku pacjenta i jak zakotwiczenie wpływa na podpowiedzi.
Pytanie 1 z 8
In Kanjee and colleagues' 2023 test of GPT-4 on NEJM clinicopathological cases, about how often was the final diagnosis anywhere in the model's differential?
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Odpowiedzi i wyjaśnienia pojawiają się w miarę rozwiązywania quizu.
- In Kanjee and colleagues' 2023 test of GPT-4 on NEJM clinicopathological cases, about how often was the final diagnosis anywhere in the model's differential?
- About 39 percent
- About 64 percent
- About 92 percent
- About 15 percent
- What was the main result of the 2024 Goh et al. randomized trial?
- Physicians given GPT-4 scored far higher than those without it
- GPT-4 alone performed worse than every physician
- Giving physicians GPT-4 did not significantly improve their diagnostic reasoning scores, although GPT-4 alone scored higher
- The trial was stopped for patient harm
- Why can vignette benchmarks overstate how well a model would do with real patients?
- Vignettes arrive with the relevant findings already chosen and cleaned up, and published cases may be in training data
- Vignettes are always written in another language
- Real patients have fewer symptoms than vignettes
- Models cannot read case descriptions longer than a paragraph
- A clinician asks, "Could this be lupus?" at the start of her prompt. Which failure mode does this invite?
- Invented laboratory reference ranges
- Refusing to answer medical questions
- Losing the conversation history
- Sycophantic anchoring toward the diagnosis the user suggested
- Why is scoring "correct diagnosis anywhere in the list" a flawed measure?
- It rewards long lists, which can prompt unnecessary testing
- It ignores the patient's age
- It only works for pediatric cases
- It requires the model to cite references
- Getting two differently ordered lists from nearly identical prompts shows what about the model's ranking?
- The model is broken and should not be used
- The second answer is always the correct one
- The ranking is not a calibrated probability estimate and shifts with wording
- The model is searching the live internet
- What is the main privacy concern with pasting a patient's chart into a consumer chatbot?
- The chatbot will refuse clinical questions
- Entering identifiable information without a business associate agreement can breach HIPAA
- Consumer chatbots cannot read lab values
- It automatically bills the patient's insurer
- Which prompt request best helps a clinician act on a model's differential?
- "Give me the single correct diagnosis"
- "Confirm my diagnosis is right"
- "Write the discharge summary"
- "List supporting and contradicting features for each item and the test that best separates the top candidates"