Data Science, Machine Learning (ML), and Artificial Intelligence (AI) have without doubt become hot topics across all industries, including healthcare. Companies, large and small, are rushing to stock up on data scientists, but are data scientists alone enough to build a successful data science practice in healthcare? Without a doubt, data scientists are needed to build models. Thanks to the increasing availability of genomics and other biomedical data, many machine learning approaches have been proposed for a wide range of therapeutic discovery and development tasks.

In the era of eHealth and personalized medicine, “big data” and “machine learning” are increasingly becoming part of the medical world. Algorithms are capable of supporting diagnostic and therapeutic processes and offer added value for both healthcare professionals and patients.