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AI / Machine Learning

Cleveland Clinic Deploys AI to Transform Clinical Trial Recruitment

AI/Machine Learning

Cleveland Clinic has launched a system-wide rollout of Dyania Health’s Synapsis AI platform following a series of successful pilot programs in cardiology, oncology, and neurology. The deployment signals a growing commitment to integrating medically trained large language models (LLMs) into clinical research workflows to accelerate trial recruitment and improve patient access to experimental therapies.

Photo 99012060 / Cleveland Clinic © Tracy Evans | Dreamstime.com

Gregg Killoren of Xsolis: How Hospitals and Health Systems Can Maintain Trust in a World of Rapid AI Adoption

AI/Machine Learning

The rapid adoption of artificial intelligence (“AI”) tools across the healthcare industry has vast potential to save both providers and payers time and money, simultaneously improving patient encounters and outcomes. Yet rapid adoption necessarily requires additional duties: namely, to use AI tools responsibly (AI governance), and to communicate to all parties, especially patients, how they’re being used (AI transparency).

ID 354316818 © Retrosesos | Dreamstime.com

AI’s Growing Influence on Provider Choice Demands a Rethink of Patient Access Strategies

AI/Machine Learning

As generative AI becomes more integrated into daily life, a growing number of patients are turning to it for healthcare decision-making, particularly in choosing providers. A new survey from rater8 reveals that nearly one-third of patients now use AI tools to research doctors, and more than one-quarter report that AI directly influenced their provider selection.

The Future of AI in Healthcare Will Be Won in the Workflow

Ben Scharfe’s interview offers a grounded view of AI’s role in healthcare today. Instead of treating AI as a monolithic solution, he frames it as a set of targeted, specialty-aware tools designed to enhance, not replace, clinician performance.

Ben Scharfe of Altera Digital Health on Targeted AI Adoption in Healthcare

Artificial intelligence is moving rapidly into healthcare workflows, but as explored in last week’s HIT Leaders & News editorial AI in Healthcare Is Moving Fast but Trust Is Moving Slowly, technology readiness does not guarantee successful adoption.

AI Agents Are Entering the Frontlines of Patient Experience

As artificial intelligence transitions from back-end optimization to frontline engagement, a new collaboration between Stanford Health Care and Qualtrics is positioning AI agents not just as workflow tools, but as direct actors in patient-facing care navigation. The effort aims to unify operational, social, and experiential data into a single, proactive layer of automation, capable of identifying missed appointments, arranging transportation, and translating instructions across linguistic or cultural barriers.

AI Is Becoming the Front Door to Complex Care

Venture-backed digital health platforms are no longer positioning AI as an assistive tool within existing care models. Increasingly, they’re building entire care infrastructures around it. Two newly funded startups, like Citizen Health and Isaac Health, are taking different but complementary approaches to this shift, using AI to reengineer access, navigation, and outcomes for historically underserved populations. Together, their strategies signal a broader industry recalibration: AI is becoming the care journey.

Photo 210434732 | Health Information © Noipornpan | Dreamstime.com

AI in Healthcare Is Moving Fast but Trust Is Moving Slowly

Artificial intelligence is no longer a theoretical capability for healthcare systems. It has moved beyond pilot projects and vendor demonstrations into live, day-to-day workflows. From pre-visit patient history summarization to automated claims processing, AI is showing up in both the exam room and the back office.

Pediatric AI Safety Anxiety Tests Regulators and Hospitals

Hospitals have spent the past decade welcoming artificial-intelligence decision tools into emergency rooms and ICUs; now many executives confess the rollout moved faster than the evidence. The patient-safety watchdog ECRI put “unproven AI in direct-care settings” at the top of its 2025 Health Technology Hazards list, warning that children are “most likely to suffer disproportionate harm.” (ECRI and ISMP)

Separating Human and AI Duties in Radiology

Artificial intelligence entered diagnostic imaging with predictions of either superseding radiologists or amplifying their productivity. A Radiology editorial by Pranav Rajpurkar and Eric Topol argues that neither extreme matches current reality. Field surveys from HIMSS show eight in ten U.S. health systems have piloted at least one imaging algorithm, yet most frontline readers remain uncertain when to rely on machine guidance.

AI Care Managers Shift Healthcare’s Administrative Frontier

Sword Health built its reputation on digital musculoskeletal therapy, winning large employer contracts in the process. The company’s latest move establishes a new division, Sword Intelligence, that pivots proven in-house automation tools toward the broader provider, payer, and public-sector markets.

Certification Is Coming for Healthcare AI. Will Systems Be Ready?

The rapid expansion of artificial intelligence in healthcare has outpaced the guardrails needed to ensure its responsible use. With clinical applications of AI now spanning from diagnostics to administrative optimization, the long-promised benefits of data-driven care are beginning to materialize.

Older Adults Are the Tipping Point in AI’s Healthcare Adoption Curve

New polling from the University of Michigan places older adults at the epicenter of artificial intelligence adoption. Far from disengaged, this demographic is experimenting with chatbots, voice assistants, and security systems, yet remains unconvinced that the benefits of AI outweigh the risks. That combination of curiosity and caution now shapes a decisive inflection point for health-care delivery, policy design, and product strategy.

AI Will Replace Your Job, Rewrite Healthcare, and Run the White House

When OpenAI CEO Sam Altman told the Federal Reserve that entire job categories would “totally, totally” disappear, it was not a prediction. It was a declaration. Speaking at the Capital Framework for Large Banks conference, Altman made it clear that AI is not waiting for permission. It is already eliminating roles, redefining diagnostic standards, and setting the terms for national economic policy.

emtelligent’s Tim O’Connell on Mitigating Risks in Responsible AI for Healthcare

In most health systems, data science answers to analytics, compliance lives with legal counsel, and clinical informatics reports to the CIO. Fragmentation of that kind throttles strategic scale. Tim O’Connell’s experience leading natural-language-processing vendor emtelligent shows that responsible AI accelerates only when those silos converge under a formal governance council chartered by the board or executive committee.