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Microsoft and Mayo Clinic Collaborate on AI Health Model

In a significant development for healthcare technology, Microsoft and Mayo Clinic have announced a collaboration to create an AI model specifically trained on medical data. This initiative aims to address the growing trend of individuals turning to AI for health-related inquiries, which can sometimes result in unreliable advice due to the broad training data of existing AI chatbots.

Focus on Medical Expertise

The new AI model will be trained using Mayo Clinic’s extensive medical records, research, and clinical expertise. According to Mayo Clinic CEO Gianrico Farrugia, the goal is to ensure that the AI provides accurate and beneficial healthcare information. The model is expected to enhance tools for clinicians and potentially be licensed to other healthcare institutions.

Initially, the AI will be available to Mayo Clinic professionals for testing. The organizations anticipate that it will take several years to refine the model to a point where it can be trusted for high-stakes health questions. The collaboration also seeks to develop an AI healthcare assistant for patient use through Mayo Clinic’s online portal.

Addressing Healthcare Needs

Microsoft AI CEO Mustafa Suleyman emphasized the long-term commitment both parties are making to this project. The initiative is part of a broader effort by major AI companies to dominate the health advice space, with competitors like Google, Anthropic, and OpenAI also developing health-focused AI tools.

Mayo Clinic’s experience with complex medical conditions and its high-quality data are expected to give this project a competitive edge. The clinic has previously utilized AI for specific medical applications, such as detecting heart disease and diagnosing pancreatic cancer.

Farrugia expressed optimism about AI’s potential to improve healthcare outcomes, acknowledging the valid concerns surrounding AI but advocating for its use to meet the global demand for better healthcare.


Original reporting: El Paso News (HLL/CB) — read the source article.

OBBM Network Editorial Staff

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Editorial team behind OBBM Network — independent, hyper-local journalism syndicated through HyperLocalLoop and OBBM Network TV.

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