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Microsoft AI system diagnoses complex cases better than human doctors – and for less money

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Research on AI for medicine looks increasingly promising — the tech already speeds up drug development, Google is using AI to improve its medical advice, and wearable companies are leveraging the technology for predictive health features. Now, Microsoft is the latest to move the goal post. 

On Monday, the company announced in a blog post that Microsoft AI Diagnostic Orchestrator (MAI-DxO), its medical AI system, successfully diagnosed 85% of cases in the New England Journal of Medicine (NEJM). This rate of diagnosis is more than four times higher than human physicians. NEJM cases are particularly complex and often require several specialists.

Also: OpenAI’s HealthBench shows AI’s medical advice is improving – but who will listen?

Given how inaccessible, complex, and confusing healthcare systems continue to be, it’s no surprise people are seeking help from technology wherever possible. 

“Across Microsoft’s AI consumer products like Bing and Copilot, we see over 50 million health-related sessions every day,” Microsoft said in the announcement. “From a first-time knee-pain query to a late-night search for an urgent-care clinic, search engines and AI companions are quickly becoming the new front line in healthcare.”

How it works 

Human physicians must pass the US Medical Licensing Examination (USMLE) to practice medicine, a test that’s also used to evaluate how AI systems perform in medical contexts, both model-to-model and when compared with humans. 

Currently, AI scores well on the USMLE — a side effect, Microsoft said, of the models memorizing (rather than understanding) answers to multiple-choice questions, which won’t produce the most sound medical analysis. Most industry-standard AI benchmarks have been saturated for a while, meaning AI models are evolving too quickly for the tests to be usefully challenging. 

To combat this issue, Microsoft created the Sequential Diagnosis Benchmark (SD Bench). Sequential diagnosis is a process real clinicians use to diagnose patients by beginning with how their symptoms present and proceeding with questions and tests from there. The test presents diagnostic challenges from 304 NEJM cases, which humans and AI models can use to ask questions. 

Also: Anthropic says Claude helps emotionally support users – we’re not convinced

Microsoft then paired the diagnostic agent, MAI-DxO, with several frontier models, including GPT, Llama, Claude, Gemini, Grok, and DeepSeek, and put the agent to the SD Bench test. MAI-DxO turns whatever LLM it is using into a “virtual panel of physicians with diverse diagnostic approaches collaborating to solve diagnostic cases,” Microsoft explained.

In a video demo, MAI-DxO also shows its reasoning as it queries the benchmark, develops possible diagnoses, and tracks the cost of each requested test. Once the agent has the required information from the benchmark about the case, it changes its diagnoses, asking for different scans and displaying a diagnostic process much more familiar to human physicians. 

Correct diagnoses that cost less

“MAI-DxO boosted the diagnostic performance of every model we tested,” said Microsoft’s blog post, noting that the system performed best when paired with OpenAI’s o3 model. The company compared the results to those of 21 physicians from the UK and the US with experience ranging from five to 20 years, who reached a mean accuracy of just 20%.

Also: You shouldn’t trust AI for therapy – here’s why

Microsoft noted that MAI-DxO is also configurable, meaning it can run within cost limitations set by a user or organization — a feature that lets the agent run a cost-benefit analysis of certain tests, which is highly relevant to the astronomical pricing of US medical care and something human doctors and patients have to consider as well. 

This feature is also a guardrail, of sorts — without it, the AI might “default to ordering every possible test — regardless of cost, patient discomfort, or delays in care,” the blog post explained. MAI-DxO also returned higher accuracy and lower costs than individual models or human physicians. 

Will AI replace your doctor?

Probably not anytime soon — though Microsoft’s blog post noted that because of its breadth of knowledge, AI can surpass “clinical reasoning capabilities that, across many aspects of clinical reasoning, exceed those of any individual physician.” 

The company believes systems like this one can “reshape healthcare” by giving patients the option to check themselves reliably and help doctors with complex cases. The cost savings would be another plus for an industry constantly plagued by inexplicably high costs and opaque pricing structures. 

Also: AI is relieving therapists from burnout. Here’s how it’s changing mental health

Microsoft conceded that MAI-DxO has only been tested on these special cases, so it’s unclear how it would handle everyday tasks. However, this issue may not be relevant anyway if the agent isn’t intended to replace human doctors, which Microsoft also maintained in the blog post. 

MAI-DxO is part of a “dedicated consumer health effort” Microsoft AI initiated last year, the company said in the release. Other AI products within that initiative include RAD-DINO, a radiology workflow tool, and Microsoft Dragon Copilot, a voice AI assistant designed for medical professionals. 





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The Greatest First Basemen of All Time According to Artificial Intelligence

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July 7, 2025

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In the intricate dance of Major League Baseball, the first baseman stands as a unique blend of offensive powerhouse and defensive anchor. They are the receivers of throws, the stretchers for outs, and often, the most prolific sluggers in the lineup. But who among these giants of the diamond truly represents the pinnacle of the position? Leveraging vast datasets of offensive metrics, defensive prowess, awards, and historical impact, Artificial Intelligence has meticulously analyzed the MLB careers of baseball’s greatest first basemen. The result is a definitive ranking of the top, based on an impartial assessment of their unparalleled contributions to the game.



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I asked ChatGPT to help me pack for my vacation – try this awesome AI prompt that makes planning your travel checklist stress-free

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2 hours ago

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July 7, 2025

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It’s that time of year again, when those of us in the northern hemisphere pack our sunscreen and get ready to venture to hotter climates in search of some much-needed Vitamin D.

Every year, I book a vacation, and every year I get stressed as the big day gets closer, usually forgetting to pack something essential, like a charger for my Nintendo Switch 2, or dare I say it, my passport.



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Denodo Announces Plans to Further Support AI Innovation by Releasing Denodo DeepQuery, a Deep Research Capability — TradingView News

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3 hours ago

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July 7, 2025

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PALO ALTO, Calif., July 07, 2025 (GLOBE NEWSWIRE) — Denodo, a leader in data management, announced the availability of the Denodo DeepQuery capability, now as a private preview, and generally available soon, enabling generative AI (GenAI) to go beyond retrieving facts to investigating, synthesizing, and explaining its reasoning. Denodo also announced the availability of Model Context Protocol (MCP) support as part of the Denodo AI SDK.

Built to address complex, open-ended business questions, DeepQuery will leverage live access to a wide spectrum of governed enterprise data across systems, departments, and formats. Unlike traditional GenAI solutions, which rephrase existing content, DeepQuery, a deep research capability, will analyze complex, open questions and search across multiple systems and sources to deliver well-structured, explainable answers rooted in real-time information. To help users operate this new capability to better understand complex current events and situations, DeepQuery will also leverage external data sources to extend and enrich enterprise data with publicly available data, external applications, and data from trading partners.

DeepQuery, beyond what’s possible using traditional generative AI (GenAI) chat or retrieval augmented generation (RAG), will enable users to ask complex, cross-functional questions that would typically take analysts days to answer—questions like, “Why did fund outflows spike last quarter?” or “What’s driving changes in customer retention across regions?” Rather than piecing together reports and data exports, DeepQuery will connect to live, governed data across different systems, apply expert-level reasoning, and deliver answers in minutes.

Slated to be packaged with the Denodo AI SDK, which streamlines AI application development with pre-built APIs, DeepQuery is being developed as a fully extensible component of the Denodo Platform, enabling developers and AI teams to build, experiment with, and integrate deep research capabilities into their own agents, copilots, or domain-specific applications.

“With DeepQuery, Denodo is demonstrating forward-thinking in advancing the capabilities of AI,” said Stewart Bond, Research VP, Data Intelligence and Integration Software at IDC. “DeepQuery, driven by deep research advances, will deliver more accurate AI responses that will also be fully explainable.”

Large language models (LLMs), business intelligence tools, and other applications are beginning to offer deep research capabilities based on public Web data; pre-indexed, data-lakehouse-specific data; or document-based retrieval, but only Denodo is developing deep research capabilities, in the form of DeepQuery, that are grounded in enterprise data across all systems, data that is delivered in real-time, structured, and governed. These capabilities are enabled by the Denodo Platform’s logical approach to data management, supported by a strong data virtualization foundation.

Denodo DeepQuery is currently available in a private preview mode. Denodo is inviting select organizations to join its AI Accelerator Program, which offers early access to DeepQuery capabilities, as well as the opportunity to collaborate with our product team to shape the future of enterprise GenAI.

“As a Denodo partner, we’re always looking for ways to provide our clients with a competitive edge,” said Nagaraj Sastry, Senior Vice President, Data and Analytics at Encora. “Denodo DeepQuery gives us exactly that. Its ability to leverage real-time, governed enterprise data for deep, contextualized insights sets it apart. This means we can help our customers move beyond general AI queries to truly intelligent analysis, empowering them to make faster, more informed decisions and accelerating their AI journey.”

Denodo also announced support of Model Context Protocol (MCP), and an MCP Server implementation is now included in the latest version of the Denodo AI SDK. As a result, all AI agents and apps based on the Denodo AI SDK can be integrated with any MCP-compliant client, providing customers with a trusted data foundation for their agentic AI ecosystems based on open standards.

“AI’s true potential in the enterprise lies not just in generating responses, but in understanding the full context behind them,” said Angel Viña, CEO and Founder of Denodo. “With DeepQuery, we’re unlocking that potential by combining generative AI with real-time, governed access to the entire corporate data ecosystem, no matter where that data resides. Unlike siloed solutions tied to a single store, DeepQuery leverages enriched, unified semantics across distributed sources, allowing AI to reason, explain, and act on data with unprecedented depth and accuracy.”

Additional Information

  • Denodo Platform: What’s New
  • Blog Post: Smarter AI Starts Here: Why DeepQuery Is the Next Step in GenAI Maturity
  • Demo: Watch a short video of this capability in action.

About Denodo

Denodo is a leader in data management. The award-winning Denodo Platform is the leading logical data management platform for transforming data into trustworthy insights and outcomes for all data-related initiatives across the enterprise, including AI and self-service. Denodo’s customers in all industries all over the world have delivered trusted AI-ready and business-ready data in a third of the time and with 10x better performance than with lakehouses and other mainstream data platforms alone. For more information, visit denodo.com.

Media Contacts

pr@denodo.com



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