NextMed Health @NextMedHealth

Welcome to Veterinary.Health. We’re building a searchable home for veterinary technology, digital health, and AI solutions for veterinarians and pet parents. Explore the growing directory: veterinary.health #VeterinaryMedicine #AnimalHealth #VetTech #PetHealth

Federal health officials announced a pilot program Monday to speed up early-stage clinical trials, which they say will reduce development timelines by six to 12 months, in hopes of encouraging U.S.-based trials and combating Chinese dominance in the field. statnews.com/2026/06/22/fda…

Conjoined twins separated with the help of AI... cnn.com/2026/06/21/hea…

From "Healthcare" to "Self-Care"....

Joel Selanikio @jselanikio

2 weeks ago

A Columbia ER doc wrote in @nytimes that she typed her own lab results into ChatGPT and got better care than her own doctor gave her — availability, patience, and truly customized diet and exercise steps (not just a generic handout). Her doctor's response to the labs was "book

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Compelling design m: A non humanoid looking humanoid robot…

A team of more than 80 researchers working across four continents have identified a set of proteins in the blood that accurately predict lung cancers more than 5 years before diagnosis. also early evidence that an existing anti-inflammatory drug could significantly reduce lung cancer risk in people with elevated concentrations of these proteins, linked to inflammation. nytimes.com/2026/06/04/wel…

Big progress vs cancer, folks. The kind of event curves from randomized trials that we've not seen before for a couple of the most deadly cancers. Congrats to the oncology research community for getting these trial done. #ASCO26, @ASCO

In a small, preliminary study, an experimental gene-editing treatment targeting PCSK9 dramatically lowered cholesterol levels, perhaps permanently, after just one infusion… nytimes.com/2026/05/25/hea…

A pancreatic cancer drug more than four decades in the making has cracked one of the most stubbornly lethal cancers, extending people’s lives and keeping their tumors in check for twice as long as those on regular chemotherapy. @ASCO washingtonpost.com/health/2026/05…

Gamification of health The Vitality program from life insurance company @johnhancockusa rewards policyholders with points for healthy behaviors such as going to the gym, buying healthy foods, tracking sleep, getting preventive screenings npr.org/2026/05/25/nx-…

A blood-based biological aging score was linked to significantly higher dementia risk in a study of more than 223,000 adults, with the strongest association seen for vascular dementia. studyfinds.com/blood-age-deme…

A big day for multi-agent AI to accelerate biomedical discovery, hypothesis generation, designing experiments with proof points of new candidate drugs (cancer, fibrosis, macular degeneration, antimicrobial resistance, and more) 2 @Nature reports @GoogleDeepMind @FutureHouseSF nature.com/articles/s4158… nature.com/articles/s4158…

Co-Scientist: A multi-agent AI partner to accelerate research deepmind.google/blog/co-scient…

The future of mental health isn't a single drug or app, it lies at the convergence of biomarkers, AI, and a real clinical team. I'm excited to see @meruhealth Advanced, which is bringing that convergence to a category that has needed it for a long time.

Kristian Ranta @ihqkristian

2 months ago

I lost my brother Peter to suicide. Standard psychiatry failed him. Today we launch Meru Health Advanced — the care model I wish he'd had. For the next Peter.

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Check out our updated resource page on digital health accelerators, incubators and funding programs digital.health/digital-health…

Augmenting clinicians with AI co-clinicians Amazing work from @DeepMind_Health @alan_karthi et al. deepmind.google/blog/ai-co-cli…

🧵1/ Our new study on AI and physician reasoning just came out in @ScienceMagazine. As co-senior author, I'm excited about our findings, and I do think AI will reshape medicine. But after seeing some of the discussions, I'm also worried about how our findings may be misinterpreted.

A new level of compatibility between electronic devices and living neural systems. Engineers @NorthwesternU have created printed artificial neurons that go beyond imitation and can directly interact with real brain cells. These flexible, low-cost devices produce electrical signals that closely resemble those generated by living neurons, allowing them to activate biological brain tissue. sciencedaily.com/releases/2026/…

The future of medicine is arriving faster than our training models are evolving. A student starting medical school in 2026 won’t earn their M.D. until 2030, and likely won’t finish residency or practice independently until 2033 or beyond. By then, the clinical and technological landscape will look dramatically different from the one many current curricula were designed for. We are only a few years into the #GenAI era, and already medicine is being reshaped by multimodal data, AI-assisted decision support, remote patient monitoring, digital health, and new models of continuous, personalized care—not to mention agentic health and the growing direct-to-consumer shift in health(care). So we need to ask some uncomfortable but necessary questions: How should we be selecting future physicians? What should they actually be trained to do? And how should we evaluate readiness in a world where information is abundant, AI is increasingly capable, and human judgment matters more than ever? I recently had the opportunity to keynote the leadership of the NBME, the organization behind the #USMLE exams that serve as a powerful “north star” for much of medical education. To their credit, NBME is proactively exploring the future of assessment and training. My message was simple: if the landscape of care is changing—with many clinicians already using AI to augment diagnostic and therapeutic decisions—the metrics we use to train and assess physicians, and clinicians more broadly, must evolve as well. It’s time for a kind of Flexner Report 2.0. That means moving beyond legacy training and assessment models toward medical education built for modern practice: • Real-world assessment that reflects the complexity and ambiguity of actual care • AI-enabled OSCEs and immersive simulations using virtual and augmented reality • Fluency in AI, digital health, multimodal and real-world data, nutrition, prevention, and design thinking • Training physicians not just to recall facts, but to synthesize information, ask better questions, use tools wisely, and deliver human care • Preparing clinicians not only to manage disease, but increasingly to optimize healthspan across the lifespan The key question is no longer just what we should add to the curriculum. It’s also what we should stop teaching, streamline, or offload to technology to make room for what matters most. Technology should not just be another subject in medical school. Increasingly, it will become part of the platform through which medicine is learned, practiced, and improved. The future of healthcare will not belong to those who simply know the most facts. It will belong to those who can integrate data, leverage intelligent tools, adapt continuously, and still show up with empathy, wisdom, and human connection. The transition is already underway. Are we ready to redesign medical education for the world ahead? #MedEd

APOLLO: a multimodal temporal foundation model that learns to represent a patient’s entire medical journey in a single computational space. By learning from millions of care trajectories, Apollo sees the future of each patient from their past. Trained and evaluated on 25 billion medical records from 7.2 million patients, spanning 33 years of care across 28 clinical modalities and 12 major specialties. Labs, vitals, clinical notes, diagnostic reports, pathology and hematology images, medications, and diagnoses, all fed into a single model. From @AI4Pathology et al. arxiv.org/pdf/2604.18570