Q: What is the current status of ChatGPT Health, MedGemma 1.5, and Claude for Healthcare? A: OpenAI, Google, and Anthropic launched specialised medical AI capabilities within days of each other, but none of the releases are cleared as medical devices, approved for clinical use, or available for direct patient diagnosis. Each company positions its tools as supporting clinical workflows and emphasises privacy and regulatory disclaimers rather than replacing clinical judgment. Q: How do the platforms differ in deployment and access models? A: In the medical AI developer platforms comparison, OpenAI’s ChatGPT Health is consumer-facing with a waitlist for Free, Plus, and Pro users outside the EEA, Switzerland, and the UK. Google’s MedGemma 1.5 is available as an open model via Hugging Face or managed on Vertex AI, while Anthropic’s Claude for Healthcare is offered through Claude for Enterprise aimed at institutional buyers. Q: Which platform is most appropriate for imaging-heavy workflows? A: Google’s MedGemma 1.5 supports three-dimensional CT and MRI scans as well as whole-slide histopathology images, making it the platform called out for imaging-heavy tasks. Google also reports benchmark improvements such as a 92.3% score on MedAgentBench and gains on MRI and CT classification in internal testing. Q: Can any of these tools be used for clinical diagnosis or treatment? A: No, none of the announced tools are intended for diagnosis or treatment and the companies explicitly state outputs are not meant to directly inform clinical diagnosis or patient management. The regulatory pathway is unclear and FDA oversight depends on intended use, so clinical decision support would require clearer validation and regulatory alignment. Q: What real-world use cases are organisations deploying these platforms for today? A: Institutions are concentrating on administrative workflows where errors are less immediately dangerous, such as prior authorisation reviews, claims processing, clinical documentation, and policy analytics. Examples from the article include Novo Nordisk using Claude for document automation and Taiwan’s National Health Insurance Administration using MedGemma to extract data from 30,000 pathology reports. Q: How should teams choose between OpenAI, Google, and Anthropic for a project? A: Use a medical AI developer platforms comparison to match the platform to your primary data types, workflows, and risk profile: choose Google for imaging and open tooling, Anthropic for enterprise controls and HIPAA-aligned connectors, and OpenAI for consumer reach and rapid user feedback. Start with low-risk administrative pilots, add rigorous validation on your own data, and keep human-in-the-loop gates before expanding to higher-impact support. Q: What validation and governance steps are recommended beyond benchmark scores? A: Treat leaderboards and benchmarks as screening tools rather than proof, run retrospective and prospective tests on your own data, and measure specific error types including misses and false alarms. Also log prompts and outputs for auditing, implement human review gates and clear rollback paths, and monitor model drift with retraining plans. Q: What regulatory and liability concerns should organisations consider when adopting these platforms? A: Regulatory frameworks vary by market and remain ambiguous; while the FDA and Europe’s Medical Device Regulation offer paths for software as a medical device, many regulators in APAC have not issued specific guidance on generative AI diagnostic tools. Liability allocation is unresolved in practice, so organisations should map PHI flows, confirm HIPAA and SOC 2 where applicable, and define harm scenarios and mitigation steps before deployment.