Big and Deep Hype and Hope: On the Special Issue for Deep Learning and Big Data in Healthcare

José Luis Rojo-Álvarez

doi:10.3390/app9204452

José Luis Rojo-Álvarez

Open Access

https://doi.org/10.3390/app9204452

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Abstract

Deep Learning networks are revolutionizing both the academic and the industrial scenarios of information and communication technologies...

Highlights

Deep Learning networks are revolutionizing both the academic and the industrial scenarios of information and communication technologies. Their theoretical maturity and the coexistence of large datasets with computational media is making this technology available to a wide community of makers and users, and recent evolution has been remarkable in techniques such as deep belief networks, Boltzmann machines, auto encoders, or recurrent networks
Healthcare is an open field for advantageous use of deep learning and big data advancements, and challenges are open in order to provide systems that can be accurate enough to be useful to the clinician and the patient in the health itinerary
The feature interpretation remains an open issue in deep learning and big data state-of-the-art, but it takes special relevance in healthcare applications in order to gain confidence in their use both by the healthcare staff and by the patients; so contributions including insights into this hot and open topic have naturally been provided

Summary

Introduction

Deep Learning networks are revolutionizing both the academic and the industrial scenarios of information and communication technologies. In a different yet often closely related arena, the analysis of large amounts of data from the Electronic Health Recording, the Hospital

Results

Conclusion