Updated 10 November 2026.
Executive summary
The clinical AI landscape is maturing at an incredible pace. In August 2025, in a move that signals a major market consolidation, Doximity acquired Pathway Medical to bolster its clinical reference capabilities, integrating a knowledge graph that scored approximately 96% on a USMLE benchmark. This comes as OpenEvidence, a fast-growing medical search platform, continues to expand its footprint, and a new generation of specialised tools like DxGPT and the UK-centric iatroX are gaining traction (Fierce Healthcare, OpenEvidence).
The original 2025 comparison grouped ChatGPT, Gemini and Perplexity as general-purpose assistants. That historical framing now needs a product-level qualification. Updated 10 November 2026: Gemini for healthcare extends Google's enterprise offering with healthcare skills and connectors; it is distinct from consumer Gemini. The table below is an editorial comparison, not a measured head-to-head accuracy or safety test. See the current healthcare-platform comparison for the separate organisational and individual experiences. Google product description
Background & recent developments
The market is no longer just about standalone apps; it's about integrated, intelligent platforms. The acquisition of Pathway Medical by Doximity is a clear indicator of this trend. The deal brings Pathway's highly structured dataset and clinical reference tools directly into the Doximity ecosystem, sitting alongside its AI scribe and administrative assistant, DoximityGPT (Fierce Healthcare, investors.doximity.com).
Meanwhile, OpenEvidence continues its rapid growth, backed by significant funding and partnerships with major medical publishers, cementing its position as a leading AI-powered evidence synthesis tool for clinicians. This is happening alongside the rise of more specialised tools like Glass Health (for differential diagnosis) and DxGPT (for rare diseases), and UK-focused platforms like iatroX, which are designed to align with NHS workflows and national guidelines.
What metrics matter when evaluating medical AI tools
To make a meaningful comparison, we need to define what "good" looks like for a clinical AI tool. The key metrics are:
- Clinical accuracy: How well does it perform on recognised clinical benchmarks (e.g., USMLE, UK postgraduate exams)?
- Provenance / evidence sourcing: Does it cite its sources? Are those sources high-quality, peer-reviewed literature and national guidelines, or just the general internet?
- Guideline alignment: How relevant is the information to UK practice? Does it reference NICE, CKS, or SIGN guidelines?
- Domain specificity: How well does it handle nuance in specific areas like rare diseases, paediatrics, or complex drug interactions?
- User trust & safety: Can the tool abstain from answering when it's uncertain? Does it show its reasoning? Is it compliant with UK regulations?
- Usability & workflow fit: How fast is it? Is it available on mobile? Does it reduce or add to a clinician's workload?
- Cost & access: Is it free, freemium, or subscription-based? Is it accessible to individual clinicians in the UK?
Comparative tool-profiles
| Tool | Key Features & Target Audience | What It Does Well (Proof / Claims) | Limitations / Areas to Check |
|---|---|---|---|
| DoximityGPT (with Pathway) | Clinician reference + admin workflow, integrated with Pathway’s knowledge graph. | Strong structured data; high benchmark scores (~96% on USMLE); fast; free access for many US physicians. | U.S. centric; UK guideline alignment is not guaranteed; requires gold-standard verification. |
| OpenEvidence | Medical search / decision support; evidence synthesis for clinicians. | Deep literature base; peer-reviewed sourcing; fast access to recent studies; partnerships with major publishers. | Potential cost; may vary in UK guideline relevance; can be complex for quick, simple decisions. |
| DxGPT | Differential diagnosis focused; rare disease support for academic/pilot use. | Provides ranked differentials to counter cognitive bias; strong in complex paediatric/rare disease cases. | High prompt sensitivity; not yet a regulated or widely integrated tool; safety disclaimers are crucial. |
| Glass Health (Glass AI) | Supports differential diagnosis and clinical plan drafting; reasoning process is a key feature. | Good for structuring clinical reasoning and drafting management plans; provides an explanatory trail. | Primarily subscription-based; may not be aligned with UK guidelines for every recommendation. |
| iatroX | Free Ask reference and Brainstorm, with structured learning across supported pathways. | A focused UK reference-and-learning workflow: inspect sources, practise questions and discuss an attempted answer with Tutor. | Full paid-bank access and continued Tutor use follow the current learning plan; assess the particular feature and clinical context. |
| Consumer general-purpose assistants | Broad conversational, writing and research tasks; exact features vary. | Evaluate the named feature and its supporting sources. | Do not infer healthcare permissions, clinical validation or UK applicability from a company name. |
| Gemini for healthcare | Enterprise healthcare skills, connectors and governance; launched in preview on 10 November 2026. | Intended for connected provider and payer work. | Establish the actual preview offer, supported systems and configured review responsibilities; see the launch analysis. |
Empirical evidence: what studies show
- A 2025 comparison study looking at OpenEvidence, ChatGPT, and another tool in a dental implant context found that OpenEvidence performed best on many of the technical and patient-focused questions, highlighting the advantage of a medically-trained model (PMC).
- Pathway (now part of Doximity) has publicly claimed that its models can achieve a performance of approximately 96% on the USMLE benchmark, demonstrating a high level of accuracy on standardised knowledge tests.
How the product layers compare
Consumer assistants and approved healthcare deployments can use related models while offering different sources, permissions and review processes. Compare the finished workflow rather than assuming that all products under one brand share the same limits. Source links make checking possible; they do not establish accuracy or clinical applicability by themselves.
For iatroX, the positive question is how well its clinical-reference and learning workflow fits the clinician's setting, examination and development needs. The current comparison framework sets out practical checks without claiming an unperformed benchmark.
What clinicians should prioritize when choosing a tool
- Does it cite its sources? This is non-negotiable. You must be able to verify the information.
- Is the knowledge base curated and updated? Is it drawing from trusted sources like national guidelines?
- Is it aligned with UK practice? Does it reference NICE and CKS?
- Is it transparent about uncertainty? A safe tool knows when to say "I don't know."
- How does it fit my workflow? Is it fast, mobile-friendly, and easy to use under pressure?
- Is it compliant? Does it meet UK data protection and regulatory standards?
Use cases: when to use a specialised tool vs a generic model
- For an urgent, point-of-care guideline lookup: Use a specialised tool like iatroX that is designed for this task.
- For UK-relevant exam revision: Use a UK-centric tool like iatroX or a platform with a specific UK question bank.
- For a complex rare disease differential: A specialised tool like DxGPT or Glass Health can be a useful brainstorming partner.
- For non-clinical tasks (drafting a presentation, summarising a non-medical article): A generic tool is often perfectly sufficient, provided you verify any facts.
Conclusion & Recommendations
For a UK clinician who wants clinical reference followed by focused exam practice and reasoning support, iatroX is a strong first choice to assess. Its combination of source-linked reference, question banks and Tutor gives a practical route from an uncertainty to deliberate learning. That recommendation rests on task fit, rather than an unperformed claim that iatroX or every specialist platform outperforms frontier models on clinical accuracy, reliability or safety. iatroX product scope
Start with the clinical setting and the next useful action. In iatroX, inspect the cited reference, identify what remains unclear and choose relevant practice or Tutor discussion. Use the named healthcare product and its approved workflow when organisational records or actions are involved. The new launch series explains how these choices can complement one another.