The European Union’s (EU) Artificial Intelligence Act (AI Act) drew a fair amount of criticism when it was first released, but Team-NB, the association of notified bodies (NBs) for the EU, has weighed in with some less than flattering observations. The group’s position paper on the legislation said that the act would not only up-classify some artificial intelligence algorithms to a higher risk class but would also resurrect the backlog of applications because of burdensome new requirements for NBs, thus exacerbating an existing crisis of med tech availability in the EU.

Researchers based at the City University of New York (CUNY) have designed a deep learning artificial intelligence (AI) model that can improve preclinical predictions of drug responses in humans. As outlined in the Oct. 17, 2022, online issue of Nature Machine Intelligence, the researchers believe their model – a context-aware deconfounding autoencoder (CODE-AE) – can help improve the quality of early drug response prediction and help reduce subsequent clinical trial failures.

Researchers based at the City University of New York (CUNY) have designed a deep learning artificial intelligence (AI) model that can improve preclinical predictions of drug responses in humans. As outlined in the Oct. 17, 2022, online issue of Nature Machine Intelligence, the researchers believe their model – a context-aware deconfounding autoencoder (CODE-AE) – can help improve the quality of early drug response prediction and help reduce subsequent clinical trial failures.

International research project Multicentre Epilepsy Lesion Detection (MELD), led by University College London, has developed artificial intelligence software that can identify minute brain anomalies that lead to epilepsy seizures. These anomalies, known as focal cortical dysplasia, can often be treated with surgery but are difficult to visualize on an MRI.