# Medicine Published articles for Medicine. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Lifesaving Lincoln Laboratory device wins 2026 Excellence in Technology Transfer Award DevFeed: [Lifesaving Lincoln Laboratory device wins 2026 Excellence in Technology Transfer Award]() Original publisher: [Read original article]() Author: Erin Lee | Lincoln Laboratory Published: 2026-09-11T13:45:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [Development](), [Software]() Tags: [2026](), [ai](), [ai-assisted-catheterization-device](), [ai-guide](), [artificial-intelligence](), [asha-rajagopal](), [autonomus-medical-technologies](), [awards-honors-and-fellowships](), [devices](), [emergency-medicine](), [engineering](), [excellence-in-technology-transfer-awards](), [federal-laboratory-consortium-for-technology-transfer](), [field](), [funding](), [health-sciences-and-technology](), [industry](), [invention](), [lincoln-laboratory](), [mass-general-hospital](), [medical-device-invention](), [medical-devices](), [medicine](), [mgh](), [military-medics](), [mit-intellectual-property](), [mit-lincoln-laboratory](), [mit-startups](), [mit-technology-licensing-office-tlo](), [national-institutes-of-health-nih](), [nih-funding](), [portable](), [prototype](), [real-world](), [research](), [samuel-kesner](), [startup](), [startups](), [technology](), [u-s-armed-forces](), [u-s-army]() ### AI overview AI-GUIDE, a portable catheterization device developed by MIT Lincoln Laboratory and Massachusetts General Hospital, received the Federal Laboratory Consortium's 2026 Excellence in Technology Transfer Award. The project is transferring its prototype to AutonomUS Medical Technologies for commercialization. ### Source excerpt The handheld catheterization device AI-GUIDE, created by Lincoln Laboratory and Massachusetts General Hospital, promises improved health outcomes for injured service members and civilians. ## The benefits of medical AI assistance vary based on user expertise DevFeed: [The benefits of medical AI assistance vary based on user expertise]() Original publisher: [Read original article]() Author: Adam Zewe | MIT News Published: 2026-08-04T09:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Artificial Intelligence](), [Human-AI evaluation](), [AI Development](), [AI Chat]() Tags: [ai](), [artificial-intelligence](), [bias](), [computer-science-and-technology](), [decision-making](), [dermatological-diagnosis](), [diagnosing-skin-disease](), [diagnostics](), [electrical-engineering-and-computer-science-eecs](), [explainability](), [explainable-ai](), [health-care](), [human-computer-interaction](), [institute-for-medical-engineering-and-science-imes](), [jameel-clinic](), [laboratory-for-information-and-decision-systems-lids](), [large-language-model](), [machine-learning](), [marzyeh-ghassemi](), [medicine](), [research](), [technology-and-society](), [users]() ### AI overview A study found that AI assistance improved skin-disease diagnosis for non-experts and clinicians, but explainability affected users differently. Non-experts often deferred to LLM-based explanations even when the AI was wrong, while clinicians performed best with the model's prediction alone. ### Source excerpt Study finds non-experts deferred to LLM-based diagnostic assistance, even when it was wrong, while clinicians caught AI errors. ## How a medical database developed at MIT evolved into a global standard of data-sharing DevFeed: [How a medical database developed at MIT evolved into a global standard of data-sharing]() Original publisher: [Read original article]() Author: Emma Foehringer Merchant | Institute for Medical Engineering and Science Published: 2026-07-29T14:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [data](), [Database](), [datasets]() Tags: [academic](), [artificial-intelligence](), [data](), [database](), [electrical-engineering-and-computer-science-eecs](), [global-data-sharing](), [harvard-mit-health-sciences-and-technology](), [harvard-mit-health-sciences-and-technology-hst](), [health](), [health-care](), [health-data-nexus](), [health-sciences-and-technology](), [history](), [history-of-mit](), [history-of-science](), [history-of-science-and-technology](), [information-systems](), [institute-for-medical-engineering-and-science-imes](), [internet](), [medical-data-sharing](), [medicine](), [mimic-medical-information-marked-for-intensive-care](), [mit-imes](), [mit-rle](), [physionet](), [repositories](), [research](), [research-laboratory-of-electronics](), [school-of-engineering](), [science](), [thomas-heldt](), [tom-pollard]() ### AI overview An MIT-developed collection of digitized electrocardiogram recordings became the foundation of PhysioNet, a global repository for biomedical and clinical data. The platform now hosts hundreds of databases and supports research users worldwide. ### Source excerpt The visionary PhysioNet platform launched 25 years ago, based on a system developed at MIT in the 1970s. It has become one of the most comprehensive biomedical and clinical data repositories in existence. ## Public disclosure of C. auris outbreaks supports public health and security DevFeed: [Public disclosure of C. auris outbreaks supports public health and security]() Original publisher: [Read original article]() Author: Adam Published: 2019-04-08T00:00:00Z Content type: opinion Language: en Sources: [Shostack & Friends Blog]() Topics: [Security & Privacy](), [Cybersecurity]() Tags: [cybersecurity](), [medicine](), [public-health]() ### AI overview The article argues that hospitals and governments should publicly disclose outbreaks of resistant infections such as C. auris. It connects transparency in public health with cybersecurity, warning that hiding harmful outcomes prevents society from making informed choices and addressing risks. ### Source excerpt Secrecy isn't the best policy when it comes to public health.