DMI's ASIP — AI-Generated Sea-Ice Charts Quadruple Coverage of Greenland's Coastal Waters
Greenland
DMI's ASIP uses a convolutional neural network fusing Sentinel-1 radar and AMSR2 microwave data to generate Greenland coastal sea-ice charts, …
Hungary · Budapest · See the Hungary profile · See the Budapest profile
Evidence: Observational / pre–post Top 6% 87/100 · Ask Evidence Copilot about this practice
MaMMa Klinika added Kheiron's Mia AI as a third reader to Hungary's national breast-screening programme. Across 25,065 women (2021-23), Mia found 24 more cancers (+7%, 83% invasive) versus double human reading, with only 70 extra recalls (+0.28%). Published in Nature Medicine.
HU110MaMMa Klinika, a private-law provider operating within Hungary's state-organised, population-based breast-cancer screening programme for women aged 45-65, added Kheiron Medical Technologies' Mia AI system as an additional reader alongside its existing double-human-reading mammography protocol, developed in partnership with Imperial College London.
Between April 2021 and January 2023, Mia was rolled out in three phases across four screening sites — a single-centre pilot, a wider multicentre pilot, and a full live clinical rollout — covering 25,065 women. When Mia's assessment disagreed with the two human readers, a senior radiologist arbitrated whether to recall the patient, without materially increasing radiologists' workload.
Across the study, Mia's involvement led to 24 additional cancers being detected compared with double human reading alone, a 7% relative increase, 83% of which were invasive. This came at the cost of only 70 additional patient recalls, a 0.28% relative increase in the recall rate. Detection gains attenuated across phases: 13% in the single-centre pilot, 10% in the wider pilot, and 5% in the full live rollout.
Published as a peer-reviewed prospective implementation study in Nature Medicine, this is one of the first papers to report AI mammography performance from routine clinical use rather than a retrospective or simulated dataset. It lacks a randomised control arm, so it describes a real-world service evaluation rather than definitive causal proof, and governance sits with a private clinical provider delivering a publicly mandated screening service rather than directly with a government agency.
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Greenland
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