Deep Learning In Biology And Medicine

Description of Deep Learning In Biology And Medicine

Biology, medicine and biochemistry have become data-centric fields for which Deep Learning methods are delivering groundbreaking results. Addressing high impact challenges, Deep Learning in Biology and Medicine provides an accessible and organic collection of Deep Learning essays on bioinformatics and medicine. It caters for a wide readership, ranging from machine learning practitioners and data scientists seeking methodological knowledge to address biomedical applications, to life science specialists in search of a gentle reference for advanced data analytics.

With contributions from internationally renowned experts, the book covers foundational methodologies in a wide spectrum of life sciences applications, including electronic health record processing, diagnostic imaging, text processing, as well as omics-data processing.

This survey of consolidated problems is complemented by a selection of advanced applications, including cheminformatics and biomedical interaction network analysis. A modern and mindful approach to the use of data-driven methodologies in the life sciences also requires careful consideration of the associated societal, ethical, legal and transparency challenges, which are covered in the concluding chapters of this book.

About the Author

Davide Bacciu is Associate Professor at the Department of Computer Science, University of Pisa, where he heads the Pervasive Artificial Intelligence Laboratory. He holds a PhD in Computer Science and Engineering from the IMT Lucca Institute for Advanced Studies, for which he has been awarded the 2009 E R Caianiello prize for the best Italian PhD thesis on neural networks.

Paulo J G Lisboa is Professor and co-Director of the School of Computer Science and Mathematics at Liverpool John Moores University. He is past chair of the Horizon 2020 Advisory Group for Societal Challenge 1: Health, Demographic Change and Wellbeing, the world’s largest coordinated research programme in health, and of the Healthcare Technologies Professional Network and JA Lodge Prize Committee in the Institution of Engineering and Technology.

Alfredo Vellido is an associate professor and former Ramón y Cajal fellow at the Department of Computer Science, Universitat Politècnica de Catalunya (UPC BarcelonaTech) in Barcelona, Spain.

Read more about: Davide Bacciu, Paulo J G Lisboa, Alfredo Vellido