Large language models (LLMs) can respond to free-text queries without being specifically
trained in the task in question, causing excitement and concern about their use in healthcare …

Scientists are enthusiastically imagining ways in which artificial intelligence (AI) tools might
improve research. Why are AI tools so attractive and what are the risks of implementing them …

AI models are increasingly applied in high-stakes domains like health and conservation.
Data quality carries an elevated significance in high-stakes AI due to its heightened …

A variety of ethical concerns about artificial intelligence (AI) implementation in healthcare
have emerged as AI becomes increasingly applicable and technologically advanced. The …

By targeting invasive organisms, antibiotics insert themselves into the ancient struggle of the
host-pathogen evolutionary arms race. As pathogens evolve tactics for evading antibiotics …

DOME: recommendations for supervised machine learning validation in biology | Nature
Methods Skip to main content Thank you for visiting nature.com. You are using a browser version …

Molecular de-extinction could offer avenues for drug discovery by reintroducing bioactive
molecules that are no longer encoded by extant organisms. To prospect for antimicrobial …

Artificial intelligence (AI) uses data and algorithms to aim to draw conclusions that are as
good as, or even better than, those drawn by humans. AI is already part of our daily life; it is …

Reticular chemistry operates in an infinite space of compositions, structures, properties, and
applications. Although great progress has been made in exploring this space through the …

Objectives To synthesise research investigating data and code sharing in medicine and
health to establish an accurate representation of the prevalence of sharing, how this …