Focus |

Machine Learning in Medicine

Machine learning has had a significant impact in many areas of science and technology, including life science and medical research. In this Focus issue, we highlight the recent advances that have been made in the development of machine learning algorithms for fundamental aspects such as statistical bioinformatics to their deployment in clinical diagnosis, prognosis and drug development.


Machine learning is swiftly infiltrating many areas within the healthcare industry, from diagnosis and prognosis to drug development and epidemiology, with significant potential to transform the medical landscape.

Editorial | | Nature Materials

Rapid progress in machine learning is enabling opportunities for improved clinical decision support. Importantly, however, developing, validating and implementing machine learning models for healthcare entail some particular considerations to increase the chances of eventually improving patient care.

Comment | | Nature Materials

At the recent Artificial Intelligence Applications in Biopharma Summit in Boston, USA, a panel of scientists from industry who work at the interface of machine learning and pharma discussed the diverging opinions on the past, present and future role of AI for ADME/Tox in drug discovery and development.

Comment | | Nature Materials

This Comment describes some of the common pitfalls encountered in deriving and validating predictive statistical models from high-dimensional data. It offers a fresh perspective on some key statistical issues, providing some guidelines to avoid pitfalls, and to help unfamiliar readers better assess the reliability and significance of their results.

Comment | | Nature Materials