Spotting skin cancer sooner with the help of artificial intelligence
Peer-Reviewed Publication
Updates every hour. Last Updated: 2-Apr-2026 15:15 ET (2-Apr-2026 19:15 GMT/UTC)
What if the earliest signs of skin cancer could be identified sooner — before a dermatology appointment?
Researchers at the University of Missouri are exploring how artificial intelligence could help detect melanoma — the most dangerous form of skin cancer — by evaluating images of suspicious skin abnormalities.
Due to their error-prone hardware, quantum computers have not yet found practical use. One promising solution is quantum error correction: special methods are used to find and correct errors in the calculations of quantum computers in order to achieve reliable results. In the snaQCs2025 project, neQxt GmbH, Fraunhofer IAF and Point 8 GmbH are working on the coordinated development of quantum error correction methods and quantum algorithms. The project aims at significantly advancing the practical applicability of quantum computers. The project kick-off took place in Cologne on January 14, 2026. The BMFTR is funding snaQCs with €2.5 million over three years.
Flue gas is exhausted from home furnaces, fireplaces and even industrial plants, and it carries polluting carbon dioxide (CO2) into the atmosphere. To help mitigate these emissions, researchers reporting in ACS Energy Letters have designed a specialized electrode that captures airborne CO2 and directly converts it into a useful chemical material called formic acid. The system performed better than existing electrodes in tests with simulated flue gas and at ambient CO2 concentrations.