Executive summary
The challenge of diagnostic uncertainty is a major patient safety issue in the UK. Studies suggest that a significant proportion of avoidable harm in both primary care and hospital settings stems from diagnostic error. As clinicians, we are trained to manage this uncertainty, but cognitive biases like anchoring and premature closure are a constant risk in a high-pressure environment (PMC, qualitysafety.bmj.com).
This is where artificial intelligence can act as a powerful new partner. While randomised trials show mixed results when physicians use a large language model (LLM) unaided, a new generation of structured AI differential diagnosis tools is emerging. When paired with authoritative clinical reference platforms like UpToDate, DynaMed, BMJ Best Practice, and VisualDx, these AI "brainstorming" tools can help clinicians widen their net, spot "don’t-miss" conditions, and build a more robust diagnostic process. The iatroX Brainstorm feature is a UK-centric tool designed for this purpose—providing a structured, ranked differential that can then be verified against trusted guidelines and evidence.
The landscape: what “AI-supported differential diagnosis” actually covers
- Brainstormers (LLM-based): These tools use generative AI to propose a list of potential diagnoses based on a clinical vignette. Examples include the UK-centric iatroX Brainstorm, Glass Health, and US-based tools like OpenEvidence’s DeepConsult.
- Authoritative references: These are the gold-standard, editorially maintained platforms designed for point-of-care use. They include UpToDate, DynaMed, BMJ Best Practice, and the dermatology-focused VisualDx. These are what you use to verify an AI's suggestions.
- Generalist LLMs: Powerful but non-medical tools like ChatGPT, Perplexity, and Grok can be used for ideation, but they carry the highest risk and require the strictest verification.
Evidence check: what studies say about LLMs and diagnosis
The evidence on ChatGPT medical accuracy and other LLMs is promising but filled with important caveats.
- A 2024 randomised trial in JAMA found that providing physicians with an LLM assistant did not consistently improve their diagnostic reasoning compared to using conventional resources. This underscores that the tool alone is not a magic bullet; the workflow and the user's skill are critical.
- Benchmarking studies show that models like GPT-4 can achieve a diagnostic accuracy of around 75% on certain case vignettes, but performance is highly dependent on the quality of the input prompt and the complexity of the case (Nature).
- A broader meta-analysis of generative AI studies found an overall diagnostic accuracy of about 52%, with parity to non-expert physicians varying significantly by clinical domain (Nature).
- Crucially, independent evaluations of ChatGPT, Gemini, and Perplexity have highlighted issues with readability and quality for clinical questions, reinforcing the non-negotiable need to verify every output (PMC).
Reference platforms you should open alongside any AI output
The safest way to use AI for differential diagnosis is to follow a simple rule: brainstorm with AI, then verify in the references. Your primary verification tools should be:
- UpToDate: The global standard for expert-authored, evidence-graded topics, perfect for working up complex cases.
- DynaMed: Known for its concise, graded recommendations and clear "Approach to..." topics for common presentations.
- BMJ Best Practice: An excellent point-of-care tool with step-by-step symptom evaluation guides and integrated calculators.
- VisualDx: An indispensable, image-rich differential generator for any dermatological presentation or skin manifestation of systemic disease.
iatroX Brainstorm for learning (UK/NHS)
The iatroX Brainstorm feature is a structured differential diagnosis tool designed with the UK clinician in mind, particularly for education and training.
- What it does: You input the key features of a case, and the tool returns a ranked list of potential differentials, suggests initial investigations, and highlights critical "don’t-miss" conditions, all designed to augment your own clinical judgment.
- How you verify: Every concept generated is linked to the iatroX Knowledge Centre, which provides a fast route to the relevant national guidelines and peer-reviewed evidence, allowing for a seamless, citation-first verification check.
- The education angle: It is explicitly designed as a "Brainstorming mode" to help you practise clinical reasoning. It is an ideal tool for trainees to rehearse case construction before a tutorial or for preparing to present to a senior.
Using general LLMs (ChatGPT, Perplexity, Grok) safely and productively
Generalist tools are great for generating a wide range of ideas, but they are not a source of truth.
- ChatGPT: Can be a powerful brainstorming partner, but its variable medical accuracy means you must treat its output as a set of hypotheses to be rigorously tested against your reference tools.
- Perplexity: Cites its sources by design, but these sources are from the open web and may not be authoritative or relevant to UK practice. Always check the provenance of the links it provides.
- Grok (xAI): Positioned as a real-time assistant, but its clinical applications are not yet validated. Use it with extreme caution and only for non-clinical exploration.
A practical workflow
- Frame the case with a succinct, de-identified problem representation.
- Brainstorm in iatroX Brainstorm (or a general LLM) to widen the net and surface "don’t-miss" items.
- Verify each plausible candidate diagnosis against an authoritative reference: UpToDate, DynaMed, BMJ Best Practice, or VisualDx for skin conditions.
- Decide & document: Record your final differential, your sources, and your clinical reasoning in the patient's notes.
- Learn: If the case highlighted a knowledge gap, log it for your CPD. You can use a tool like the iatroX Quiz to create a spaced repetition schedule to consolidate your learning.
Buyer’s checklist for AI differential tools
- Provenance: Does the tool provide visible citations and links to trusted UK-accepted sources? (iatroX Knowledge Centre)
- Structure: Does it provide a ranked differential, suggested investigations, and clear red-flag warnings? (iatroX Brainstorm)
- Abstention & uncertainty: Does the tool clearly state when evidence is weak or a condition is outside its scope?
- Educational value: Does it have a dedicated mode for practice and learning, not just providing answers? (iatroX Brainstorm)
Quick comparison table
| Tool | Type | Strengths | Limitations | Best Used For |
|---|---|---|---|---|
| iatroX Brainstorm | UK-centric LLM Assist | Structured DDx + UK Citations | Not a substitute for primary guidelines | Teaching & Clinic Prep |
| ChatGPT | General LLM | Fast Ideation, Flexibility | Variable Medical Accuracy, No Citations | Early Brainstorming (must verify) |
| Perplexity | Answer Engine | Cited Outputs from Web | Source quality varies; not UK-specific | Rapid Scans (verify in primaries) |
| Grok | Real-time Assistant | Broad Capabilities | Limited Clinical Validation | Non-clinical exploration only |
| UpToDate/DynaMed/BMJ | References | Evidence-Graded Topics | Subscription Access | Verification & Management |
| VisualDx | Derm Reference | Image-Rich Differentials | Narrower Scope | Skin Presentations |
FAQs
- Are diagnostic errors really that common in the UK?
- Yes. UK-based analyses attribute approximately 60% of avoidable significant harm in primary care to diagnostic error, and hospital-based estimates suggest 1 in 14 general medical inpatients suffer a harmful diagnostic error.
- Are most of these errors preventable?
- The evidence suggests yes—an estimated 85% of harmful diagnostic errors in general medical inpatients are considered preventable.
- Does AI replace my clinical judgement?
- No. Tools like iatroX Brainstorm are designed to augment your reasoning and prompt wider consideration. The final decision and responsibility always rest with you, after verifying with trusted primary sources.