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<td><span style="font-family:Helvetica, sans-serif; font-size:20px;font-weight:bold;">Health Tech | Fierce Healthcare</span></td>
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<td><a href="https://www.fiercehealthcare.com/health-tech/health-tech-weekly-rundown-tether-launches-medical-ai-phones-wearables-medaptus" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Health Tech Weekly Rundown: Perplexity, VisualDx team up</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">May 8th 2026, 13:46</div>
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<p><div class="col content" morss_own_score="5.201065246338215" morss_score="80.96958533299193">
<p>Stay up to date on the latest in health tech, digital health and health AI news with this weekly brief. This is news from the week of May 4 to May 8.</p>
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<h3>Tether launches medical AI that runs on phones, wearables</h3>
<p>Tether <a href="https://tether.io/news/tether-unveils-medical-ai-that-runs-on-phones-outperforms-much-larger-sota-models-and-can-cut-the-cloud-out-entirely/">unveiled</a> QVAC MedPsy Thursday, a new class of language models that can run directly on smartphones, wearables and other devices. </p>
<p>The company says the platform’s focus on efficiency reduces both compute requirements and reliance on remote cloud infrastructure.</p>
<p>Tether CEO Paolo Ardoino said in a statement that the launch was focused on “improving efficiency at the model level” instead of “scaling up size,” adding that the 1.7 billion-parameter model “outperformed larger systems” during testing.</p>
<p>“That combination matters because it directly reduces compute requirements, latency and cost,” Ardoino said. “It allows the model to run locally on standard hardware instead of relying on remote infrastructure. In healthcare, that changes the constraints entirely; you can run medical reasoning where the data already exists, inside a hospital system or on a device, without moving sensitive information through the cloud or waiting on external processing.”</p>
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<h3>Elation Health integrates new cardiovascular risk standard</h3>
<p>Elation Health <a href="https://www.businesswire.com/news/home/20260507755633/en/Elation-Health-Integrates-New-American-Heart-Association-and-American-College-of-Cardiology-Cardiovascular-Risk-Standard">announced</a> Thursday it has licensed the American Heart Association’s Predicting Risk of Cardiovascular Disease Events (PREVENT) risk calculator to be embedded within its AI-powered clinical decision support tool. </p>
<p>Elation’s Clinical Insights platform, powered by Anthropic’s Claude for Healthcare, ran more than 2,000 tests to ensure the implementation matches management guidelines. </p>
<p>The American Heart Association and American College of Cardiology <a href="https://newsroom.heart.org/news/accaha-issue-updated-guideline-for-managing-lipids-cholesterol">released</a> updated cholesterol and lipid management guidelines in March, which made the PREVENT calculator the primary prevention test for atherosclerotic cardiovascular disease (ASCVD).</p>
<p>“Primary care clinicians are on the front lines of prevention. Medicine moves fast, and when new clinical guidelines come out, they need technology that responds right away. We’re leading the market by setting a new standard for modern primary care technology,” said Kyna Fong, Elation Health CEO and co-founder, in a statement. “Independent practices often don't have the resources to quickly adopt new standards. We integrated PREVENT in days, so they didn’t have to wait. This isn’t just software that supports their work—it’s a platform that supports clinical excellence alongside them. When physicians can access the best tools, they can deliver better care for their patients."</p>
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<h3>Perplexity, VisualDx partner to bring medical imagery into gen AI</h3>
<p>Perplexity and VisualDx <a href="https://www.businesswire.com/news/home/20260505485878/en/VisualDx-and-Perplexity-Bring-Clinician-Trusted-Medical-Imagery-into-Generative-AI">announced</a> Tuesday a partnership that will allow Perplexity users to view clinician-validated medical images when asking health questions.</p>
<p>Users will also be able to compare similar-appearing conditions and explore diagnostic differences, better understand visual conditions and browse VisualDx to “go deeper” in differential diagnosis, testing options, treatment options and more, they said. </p>
<p>“Medicine is visual,” said Art Papier, M.D., VisualDx CEO and co-founder, in a statement. “So much of a diagnosis depends on pattern recognition and comparison. By integrating VisualDx into Perplexity, we’re helping ensure that AI health information reflects real clinical thinking that’s supported by trusted imagery, visual evidence, and transparency.”</p>
<p>The partnership marks VisualDx’s entry into Perplexity’s Premium Health Sources, which includes other organizations like the American Heart Association, The BMJ and The New England Journal of Medicine.</p>
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<h3>Medaptus launches 24/7 operational ‘command center’ for hospital medicine</h3>
<p>Medaptus <a href="https://www.prnewswire.com/news-releases/medaptus-launches-command-a-247-operational-command-center-for-hospital-medicine-302762165.html">announced</a> Tuesday the launch of Medaptus Command, a hospital operations platform aimed at coordinating medicine program workflows.</p>
<p>The platform has five capabilities: intake, assignment, distribution, reconciliation and analytics. Its capabilities are built into existing electronic health records (EHRs), according to the announcement.</p>
<p>“Hospital medicine has outgrown the tools used to run it," said Malachi Charbonneau, Medaptus' CEO, in a statement. “Command brings intake, assignment, distribution, reconciliation and analytics into sync, giving leaders real-time visibility and the efficiency to run their operations more effectively.”</p>
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<td><a href="https://www.fiercehealthcare.com/ai-and-machine-learning/op-ed-its-time-make-more-strategic-bets-ai-healthcare" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Op-ed: It's time to make more strategic bets on AI in healthcare</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">May 8th 2026, 13:46</div>
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<p>More than 230 million people turn to ChatGPT to ask questions related to health and wellness <a href="https://cdn.openai.com/pdf/2cb29276-68cd-4ec6-a5f4-c01c5e7a36e9/OpenAI-AI-as-a-Healthcare-Ally-Jan-2026.pdf">each week</a>. Meanwhile<a href="https://www.ama-assn.org/press-center/ama-press-releases/ama-ai-usage-among-doctors-doubles-confidence-technology-grows#:~:text=Center%20Press%20Releases-,AMA:%20AI%20usage%20among%20doctors%20doubles%20as%20confidence%20in%20technology,John%20Whyte%2C%20MD%2C%20MPH.">, four out of five physicians</a> are exploring the use of AI in their practices, and the large language model Claude for Healthcare, rolled out in January, is <a href="https://www.fiercehealthcare.com/ai-and-machine-learning/jpm26-anthropic-launches-claude-healthcare-targeting-health-systems-payers">poised to transform medical billing</a>. </p>
<p>As new capabilities for artificial intelligence (AI) in healthcare emerge almost daily, healthcare leaders face a paradox: urgency to adopt alongside persistent hesitation to scale.</p>
<p>There are also signs that AI could improve access to health information and guidance for vulnerable people, with <a href="https://cdn.openai.com/pdf/2cb29276-68cd-4ec6-a5f4-c01c5e7a36e9/OpenAI-AI-as-a-Healthcare-Ally-Jan-2026.pdf">600,000 health-related queries to ChatGPT</a> coming from underserved rural areas each week. </p>
<p>Yet surging capital costs continue to erode the money available for strategic investment. As a result, AI use cases in healthcare often struggle to move past the pilot stage. In this era, making the right bets on AI in healthcare depends on responsible AI strategies as well as a willingness to act quickly to seize opportunities at scale. </p>
<h3><strong>Go beyond AI experimentation</strong> </h3>
<p>Adoption of AI in healthcare <a href="https://menlovc.com/perspective/2025-the-state-of-ai-in-healthcare/?_bhlid=051bea2ab1eb0471b58d80757411ae1ac8cbe507">more than doubled the rate of adoption</a> in other industries from 2023 to 2025. </p>
<p>Optimizing AI’s business value in healthcare depends not just on deploying the right tools in the right areas, but also on scaling these tools quickly. It also necessitates careful consideration around how to move fast with AI, without putting undue stress on an already-challenged workforce. </p>
<p>For example, while agentic AI shows tremendous promise for reducing administrative burden and costs in the healthcare revenue cycle, across industries there are barriers to its adoption. One of the biggest roadblocks is the fear of being replaced by AI: a concern that <a href="https://www.ey.com/content/dam/ey-unified-site/ey-com/en-us/insights/emerging-technologies/documents/ey-wave-3-ai-pulse-survey-full-report.pdf">two out of three leaders surveyed</a> say is fueling hesitancy in agentic AI adoption. </p>
<p>And while use cases for AI are expanding in healthcare, an <a href="https://engage.klasresearch.com/blog/healthcare-ai-update-2025-the-practical-ai-use-cases-healthcare-is-scaling-today/9515/">analysis by KLAS Research</a> indicates most organizations use AI for lower-risk purposes like ambient AI to generate structured notes from physician-to-patient conversations, imaging triage, predictive risk modeling and patient message response. </p>
<h3><strong>Moving the needle on AI ROI</strong> </h3>
<p>With limited resources to invest in AI, how can healthcare leaders make the right moves for near-term and long-term value? Here are three considerations in a transformative environment. </p>
<ol><li><p><strong>Don’t just taste the tool. Chase the tools</strong>. Capital constraints demand a shift from experimentation to implementation. Rather than testing isolated tools, organizations should prioritize solutions designed to scale from the outset. For healthcare leaders, this means looking for tools that may have been built for one workflow or hospital but could transfer seamlessly to others. This approach accelerates deployment, reduces development costs and strengthens foundations for data governance and workforce adoption.</p><p>In determining which AI initiatives to pursue, it’s also important to map their value to the healthcare organization’s strategy. This helps avoid isolated AI use cases that struggle to deliver on their intended value. It also ensures that the investments an organization makes around AI are thoughtfully aligned with the health system’s mission, vision and business objectives, and carefully balance risk with rewards. </p></li><li><p><strong>Ensure that the tools you choose are compatible with the EHR</strong>. This budget-protecting approach paves the way for rapid-paced innovation through seamless integration. It also makes it easier to engage team members in an AI tool through ease of access and integration with other functions. The ability to draw from data in the EHR also provides a foundation for actionable intelligence based on data that is clean, governed and accessible. With this foundation, healthcare teams can more easily turn pain points into viable innovations that present strong potential for ROI. </p><p>In 2026, key opportunities to link AI innovation to integration in the EHR include: </p></li></ol>
<ul><li><strong>Clinical workflow improvement</strong>, including documentation, imaging and diagnostics</li><li><strong>Patient engagement</strong>, such as by enhancing patient interactions through the use of virtual assistants, AI-powered symptom checkers and educational resources </li><li><strong>Revenue cycle management</strong>, where AI can convert unstructured data into usable information and streamline prior authorization, billing, coding and denials</li></ul>
<ol><li><strong>Controls to monitor AI value</strong>. A recent EY global risk study found that organizations with real-time performance monitoring for AI initiatives are 65% more likely to achieve cost savings <em>(Editor's note: This article's author is affiliated with EY)</em>. This underscores the importance of embedding AI properly within the wider digital ecosystem and regularly tracking AI efforts with support from an AI governance committee. The committee should focus on value metrics, such as operational efficiency, quality improvement, cost reduction and patient outcomes, to ensure AI delivers measurable benefits and aligns with organizational goals.</li></ol>
<p>As the pace of AI adoption in healthcare increases, developing a roadmap for implementation that emphasizes rapid deployment and reward while reducing risk will drive momentum. It will also build team members’ confidence in innovation—critical for sustaining AI gains over the long term. </p>
<p><em>John Ward is a partner in technology consulting at EY and is head of health technology.</em></p>
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<p><strong>Forwarded by:<br />
Michael Reeder LCPC<br />
Baltimore, MD</strong></p>
<p><strong>This information is taken from free public RSS feeds published by each organization for the purpose of public distribution. Readers are linked back to the article content on each organization's website. This email is an unaffiliated unofficial redistribution of this freely provided content from the publishers. </strong></p>
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