Bioscience News - GEG Tech top picks

In a recent review published in the journal Nature Medicine, scientists discussed the results of a two-year weekly effort to track and communicate significant developments in medical AI. In particular, AI has been a game-changer in the crucial task of protein folding, which involves predicting the 3D structure of a protein from its chemical sequence. Improvements in protein structure prediction can reveal mechanistic information about a variety of events, including drug-protein interactions and mutation effects. With AI, non-invasive cancer screening, prognosis, and tumor origin identification are now possible. Moreover, deep learning has improved CRISPR-based gene editing by helping predict guide RNA activity and identifying anti-CRISPR protein families. According to one study, BioBERT, a model trained on a large corpus of medical literature, outperformed previous peers on natural language tasks such as answering biological questions.  

The US-based researchers say the new system, which is based on image recognition, could be developed for smartphones, increasing access to screening and providing a low-cost way to check whether skin lesions are cause for concern.

AI algorithms have been successfully tested in pinpointing healthy brains and those with the disease with 86 per cent accuracy, leading to hopes it could ultimately be used by the NHS to predict Alzheimer's.