AI that understands, reasons and acts: Closing the integration gap in enterprise imaging
Agentic AI assists with routing urgent scans. The description says this cuts minutes to treatment.
Read the original →Every story in this issue with a short summary, so you can decide what to read before leaving the site. Summaries are written by AI (Claude) only from each publisher's own description and checked by Jev for anything not in that description. They are not full translations. Follow "Read the original" for the full story.
Agentic AI assists with routing urgent scans. The description says this cuts minutes to treatment.
Read the original →Gout can leave lumps of crystallized uric acid, called tophi, around joints and tendons. These chalky deposits build up slowly. The story concerns an AI system that reads ultrasound images to track them.
Read the original →Over three years, researchers have built progressively harder and more realistic benchmarks for medical AI. The piece describes what they learned from this work.
Read the original →Artificial intelligence promises speed and accuracy in healthcare, but it also decides whose symptoms count. The cost may be patients' trust in their own bodies.
Read the original →Recent studies reveal measurable clinical benefits of hospital prediction systems. They also show a continuing burden of false alerts.
Read the original →Public data may help identify drugs associated with shortages. Hospital inventory and purchasing data could make early-warning tools more useful.
Read the original →The new model was trained to estimate a person's age or, for those with cancer, their survival chances.
Read the original →Notable has launched Flow Compass, which gives healthcare operators conversational control to test, monitor and govern their AI workforce. It works across EHR workflows.
Read the original →KT announced plans to pursue a medical AX business in cooperation with Acryl, a medical AI specialist. They see scope to expand AI applications beyond clinical support to data utilization, research, administration and hospital operations. Together they will work to verify the technology and develop standardised products for the industry.
Read the original →Six-foot robots are cruising grocery aisles, including at a Ralphs store. The description says shoppers who see one should not panic, as it is probably not hunting for humans.
Read the original →Insilico Medicine (HKEX: 3696), a clinical-stage generative AI-driven drug discovery company, announced it has achieved the early drug discovery milestone in its multi-year collaboration with Servier. Servier is an independent international pharmaceutical group governed by a foundation.
Read the original →Japan's Pharmaceuticals and Medical Devices Agency (PMDA) has published "review points" for medical devices using generative AI.
Read the original →Washington has ordered agencies to remove the Chinese AI firm's software, citing potential data exposure and cybersecurity vulnerabilities. Beijing accuses the US of politicising technology.
Read the original →AI-designed viruses could help scientists fight antibiotic-resistant bacteria, offering fresh hope for future treatments. The breakthrough also raises questions about biosafety, genetic engineering and public health risks.
Read the original →Mass General Brigham researchers developed FAHR-Face, a foundation AI model trained on more than 40 million facial photographs, and used it to create two tools that estimate biological age and predict survival outcomes in patients with cancer from a simple photo. The study found the model improved on the team's earlier FaceAge technology and remained robust across common photo variations, cosmetic procedures and makeup. It also found that lifestyle factors such as smoking and alcohol and drug use were associated with accelerated facial aging.
Read the original →Researchers at Mass General Brigham Cancer Institute have developed an AI system that estimates cancer patients' survival odds from a single facial image.
Read the original →The Leading-edge Semiconductor Technology Center (LSTC), in which Rapidus participates, Hokkaido University, Fujifilm and others announced on the 20th that they will jointly develop a system that processes medical images with AI. It will use advanced semiconductors for the real-time image processing required in medical settings.
Read the original →KT plans to build a foundation for standardizing and using medical data, and to jointly pursue AI service development and on-site trials. On the 20th, KT said it signed a business agreement with Acryl at Acryl's headquarters in Seonneung, Seoul, for joint promotion of the medical AI transformation business.
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