Wednesday, July 30, 2025

 

From WebMD to AI chatbots: How innovation has empowered patients to take control of their health



New analysis highlights the transformative power of digital technology in shaping the e-patient era



JMIR Publications

From WebMD to AI Chatbots: How Innovation Has Empowered Patients to Take Control of Their Health 

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New Analysis Highlights the Transformative Power of Digital Technology in Shaping the E-Patient Era

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Credit: JMIR Publications




TORONTO, ON July 28, 2025 A new research article published in the Journal of Participatory Medicine unveils how successive waves of digital technology innovation have empowered patients, fostering a more collaborative and responsive health care system. The paper, titled "From Internet to Artificial Intelligence (Al) Bots: Symbiotic Evolutions of Digital Technologies and e-Patients," explores the symbiotic evolution of digital health tools and the increasingly engaged e-patient.

The concept of the e-patient, defined as an individual "equipped, enabled, empowered, and engaged" in their health, has been propelled forward by advancements spanning the early days of the internet to the latest in AI. This evolution marks a significant shift from the traditional passive patient role to one of active participation and co-production in health care.

"Our research demonstrates a clear trajectory where each digital innovation has built upon its predecessors, providing patients with unprecedented tools for self-care and interaction with the health care system," says Dr. Danny Sands, an author of the research. "This isn't just about convenience; it's about fundamentally changing the dynamic between patients and clinicians for the better."

The article details 9 key technological innovations and their profound impact on patient empowerment:

  • The World Wide Web, which democratized access to health information and medical literature.

  • Email, which facilitated asynchronous communication between patients and providers, breaking down traditional barriers.

  • Social networking, which created peer-to-peer support communities, enabling information sharing and emotional support.

  • Electronic health records (EHRs), which enhanced safety and confidence in care, laying the groundwork for patient access to their data.

  • Patient portals, which provided direct access to medical records, secured communication with health care teams, and streamlined administrative tasks.

  • Smartphones, which offered ubiquitous access to health information, apps, and connectivity with health care resources and self-monitoring devices.

  • Patient-generated health data (PGHD), which empowered patients to contribute their own health insights from self-monitoring devices, improving self-management and clinical understanding.

  • Telemedicine and telehealth, which improved access to professional care, especially for mental health and lifestyle needs, and expanded remote care options.

  • AI, which has emerged with vast potential to help patients understand their medical records, enhance comprehension of medical literature, and assist with complex health decisions.

The researchers emphasize that the rise of the e-patient, often driven by a desire for greater control and transparency, has in turn spurred further technological development. This ongoing cycle is creating a health care system that is increasingly safer and more attuned to individual patient needs.

"While we celebrate these advancements, we also recognize the ethical challenges that new technologies, particularly AI, present," Dr. Sands adds. "Concerns around patient safety, data privacy, and equitable access remain paramount and require careful consideration as we move forward."

The study concludes that the symbiotic evolution of digital health technologies and the ascendance of the e-patient are forging a future where communication, collaboration, and coordination between patients and clinicians are significantly improved, leading to a more patient-centric health care experience.

 


About the Journal of Participatory Medicine: 

The Journal of Participatory Medicine is a peer-reviewed, open-access journal dedicated to exploring the intersection of patients and health care, with a focus on patient engagement, empowerment, and shared decision-making. The journal is also the official journal of the Society for Participatory Medicine.

 

About JMIR Publications:

JMIR Publications is a leading open access publisher of digital health research and a champion of open science. With a focus on author advocacy and research amplification, JMIR Publications partners with researchers to advance their careers and maximize the impact of their work. As a technology organization with publishing at its core, we provide innovative tools and resources that go beyond traditional publishing, supporting researchers at every step of the dissemination process. Our portfolio features a range of peer-reviewed journals, including the renowned Journal of Medical Internet Research.

 

About the Society for Participatory Medicine:

The Society for Participatory Medicine is a 501 (c)(3) not-for-profit organization devoted to promoting the concept of participatory medicine, a movement in which networked patients shift from being mere passengers to responsible drivers of their health, and in which providers encourage and value them as full partners.
 

To learn more about JMIR Publications, please visit jmirpublications.com or connect with us via TwitterLinkedInYouTubeFacebook, and Instagram.

Head office: 130 Queens Quay East, Unit 1100, Toronto, ON, M5A 0P6 Canada

Media contact: communications@jmir.org

The content of this communication is licensed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, published by JMIR Publications, is properly cited.

Mayo Clinic deploys NVIDIA Blackwell infrastructure to drive generative AI solutions in medicine




Mayo Clinic



ROCHESTER, Minn. — Mayo Clinic took a pivotal step toward integrating AI solutions in the clinical setting with the deployment of NVIDIA DGX SuperPOD with NVIDIA DGX B200 systems, an advanced infrastructure that provides state-of-the-art AI compute capabilities.

Mayo Clinic and NVIDIA collaborated to enable the rapid innovation and development of foundation models in support of Mayo’s platform approach to healthcare, contributing to Mayo Clinic’s Bold. Forward. strategy and new innovations for generative AI solutions and digital pathology. These innovations are delivering new insights as Mayo is driving to improve patient outcomes and transform healthcare.

"Our aspiration for AI is to meaningfully improve patient outcomes by detecting disease early enough to intervene. What was once a hypothetical — 'If only we had the right data' — is now becoming reality thanks to AI and advanced computing," says Matthew Callstrom, M.D., Ph.D., medical director of the Department of Strategy and leader of Mayo Clinic’s Generative Artificial Intelligence Program.

The advanced computing infrastructure will initially support foundation model development for pathomics, drug discovery and precision medicine.

The NVIDIA Blackwell-powered DGX SuperPOD is built to efficiently process large, high-resolution imaging essential for AI foundation model training. Designed for speed and scalability, the Blackwell infrastructure enables Mayo Clinic to accelerate pathology slide analysis and foundation model development — reducing four weeks of work to just one, ultimately improving patient outcomes. This advanced computing infrastructure will also advance Mayo Clinic’s generative AI and multimodal digital pathology foundation model development.

Mayo Clinic, in partnership with Aignostics, developed a leading pathology foundation model called Atlas, trained on more than 1.2 million histopathology whole-slide images. With Atlas, Mayo Clinic clinicians and researchers can improve accuracy and reduce administrative tasks. The new computing capabilities will accelerate and improve clinical model development.

"This compute power, coupled with Mayo’s unparalleled clinical expertise and platform data of over 20 million digitized pathology slides, will allow Mayo to build on its existing foundation models. We’re transforming healthcare by quickly and safely developing innovative AI solutions that can improve patient outcomes and enable clinicians to dedicate more time to patient care while also accelerating commercial affiliations with other industry leaders," says Jim Rogers, CEO of Mayo Clinic Digital Pathology.

Journalists: Media kit with images for download available here.

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About Mayo Clinic Digital Pathology
Mayo Clinic Digital Pathology facilitates the global scaling of digital pathology solutions to benefit clinicians and patients, advancing key areas such as scanning, storage, foundation model development and the creation and deployment of cutting-edge algorithms. Working with Mayo Clinic innovators and external collaborators, Mayo Clinic Digital Pathology is wholly owned by Mayo Clinic and seeks to incubate and start impactful companies while investing in and acquiring existing companies, spurring innovation across pathology.

About Mayo Clinic
Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.



Breaking research at ADLM 2025: AI poised to revolutionize Lyme disease testing, treatment




Together, these findings spotlight the potential of AI to make a profound, positive difference in people’s lives when thoughtfully integrated into clinical laboratory medicine



Association for Diagnostics & Laboratory Medicine




CHICAGO — Today at ADLM 2025 (formerly the AACC Annual Scientific Meeting & Clinical Lab Expo), researchers will unveil a blood test developed with the help of artificial intelligence (AI) that identifies Lyme disease sooner and more accurately than the current standard — and that could translate to vastly improved patient outcomes. A second study highlights how certain generative AI tools can empower adolescents by helping them to gather useful medical information.

Together, these findings spotlight the potential of AI to make a profound, positive difference in people’s lives when thoughtfully integrated into clinical laboratory medicine.

Lyme test offers hope for early, effective treatment
Each year, more than 475,000 Americans are diagnosed with Lyme disease — a number that is only expected to climb due to climate change expanding the range of areas where ticks can live. When caught early, the condition responds well to antibiotics. However, the typical test — called two-tier serology — detects early Lyme accurately only 30% of the time. It’s a significant missed opportunity, since more than half of Lyme patients not diagnosed or treated within the first few weeks of infection will develop long-term health problems such as fatigue, neurocognitive issues, and arthritis.

The new test leverages AI to offer major improvement. Its sensitivity and specificity are both over 90%, “meaning 9 out of 10 patients are going to get a correct diagnosis and receive appropriate treatment, which lowers the risk of chronic illness significantly,” said Holly Ahern, a microbiologist and chief scientific officer at ACES Diagnostics.

Ahern and team built on research in rhesus macaque monkeys, whose immune response to the bacteria causing Lyme is similar to humans, to develop a panel that looks for 10 proteins (antigens) and is completed as a single test. This approach is an improvement over the two-tier method, which may require up to four tests.

Next, they analyzed blood samples from humans, including 123 people with Lyme disease and 197 uninfected individuals, to test whether adding machine learning to the test could bolster performance by detecting unique immune patterns. “You and I might get infected by the same bacteria, but we might both produce different antibody responses to it,” said Ahern. “With these antigens matched with a decision-tree–based classifier, we can actually pick that up in each individual case.”

The team found an algorithm that improved accuracy across all disease stages, correctly flagging infection in over 90% of early cases (versus 27% with the standard method). They hope the test — which, according to Ahern, is relatively inexpensive and works on standard laboratory equipment — will be commercially available by the end of 2026.


Medicine-GPT as an informational tool for adolescents
A second study assessed Medicine-GPT, a doctor-developed, free-to-use ChatGPT custom model. The research focused on adolescents because they tend to be early tech adopters who frequently search for information online, often on topics they don’t feel comfortable discussing with adults.

“Medicine-GPT shows promise as a powerful tool for addressing adolescent health inquiries, outperforming ChatGPT-4 in completeness, reasoning, and overall medical helpfulness,” said Austin Jin, a high school research intern at Weill Cornell Medicine in New York.

Jin and team gathered over 100 clinical questions related to lab medicine and diagnostics from Reddit’s “Ask Doctors” forum, filtering for posts by people aged 10-19 and sorted by “top” interactions. They evaluated how well the customized chatbot provided useful answers compared to its predecessor, ChatGPT-4.

Both models demonstrated complete factual accuracy, but Medicine-GPT outperformed ChatGPT-4 on other measures, achieving ratings of 66.6% for completeness, 60% for reasoning, and 46.6% for helpfulness (compared to 20%, 33.3%, and 23.3%, respectively, for ChatGPT-4). Both models received high ratings on clarity (80% for Medicine-GPT vs. 70% for ChatGPT-4).

However, a common challenge is that these tools can leave teenagers feeling overwhelmed, especially when chatbots present rare, fatal conditions as diagnostic possibilities. “This highlights the need for future AI tools to not only be medically accurate, but also context-aware, user-sensitive, and aligned with how clinicians communicate,” Jin said.“Rather than discouraging use, providers can guide adolescents on how to use these tools responsibly, emphasizing that AI … should never replace professional medical advice or personalized evaluation.”

About ADLM 2025
ADLM 2025 (formerly the AACC Annual Scientific Meeting & Clinical Lab Expo) offers 5 days packed with opportunities to learn about exciting science from July 27-31 in Chicago. Plenary sessions will explore urgent problems related to clinical artificial intelligence (AI) integration, fake medical news, and the pervasiveness of plastics, as well as tapping into the promise of genomics and microbiome medicine for personalized healthcare.
At the ADLM 2025 Clinical Lab Expo, more than 800 exhibitors will fill the show floor of the McCormick Place Convention Center in Chicago, with displays of the latest diagnostic technology, including but not limited to AI, point-of-care, and automation.


About the Association for Diagnostics & Laboratory Medicine (ADLM)
Dedicated to achieving better health for all through laboratory medicine, ADLM (formerly AACC) unites more than 70,000 clinical laboratory professionals, physicians, research scientists, and business leaders from 110 countries around the world. Our community is at the forefront of laboratory medicine’s diverse subdisciplines, including clinical chemistry, molecular diagnostics, mass spectrometry, clinical microbiology, and data science, and is comprised of individuals holding the spectrum of lab-related professional degrees, certifications, and credentials. Since 1948, ADLM has championed the advancement of laboratory medicine by fostering scientific collaboration, knowledge sharing, and the development of innovative solutions that enhance health outcomes. For more information, visit www.myadlm.org.

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