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Predictors of Physical Health and Well-Being: The Role of Deep Learning

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Disease Prevention".

Deadline for manuscript submissions: closed (30 January 2024) | Viewed by 168

Special Issue Editors

Neuroscience and Behaviour Laboratory, Italian Institute of Technology, 00161 Roma, Italy
Interests: machine learning; deep learning; psychology; neurophysiology
Department of Psychology and Cognitive Sciences, University of Trento, 38100 Trento, Italy
Interests: social neuroscience; clinical psychology
Special Issues, Collections and Topics in MDPI journals
Department of Psychology and Cognitive Science, University of Trento, 38068 Trento, Italy
Interests: physiological signal processing; statistical neuroimaging; artificial intelligence; reproducibility
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

In recent years, healthcare has benefited from computational techniques to obtain insights from complex, high-dimensional, and heterogeneous biomedical data; advancements in personalized medicine, especially the prevention, diagnosis, and treatment of diseases; and health approaches to promote general well-being. Modern biomedical and well-being research can benefit from a variety of data types, including electronic health records, neurophysiological recordings, imaging data, pervasive and wearable-sensor data, and text. However, these sources are often poorly annotated and generally unstructured. As such, deep learning technologies can play a crucial role in the analysis of physical health, given the fact that they can be used to detect anomalies, analyze failures, and predict future states based on up-to-date information that does not require labeled data. 

This Special Issue of IJERPH focuses on the current state and novel applications of deep learning techniques for studying physical health. New research papers, reviews, and case reports are welcome, as well as papers dealing with new approaches and applications of deep learning models in the healthcare field. Other manuscript types accepted include methodological papers, position papers, brief reports, and commentaries.

We will accept manuscripts from different disciplines including neuroscience, machine learning, deep learning, healthcare, and physical health. Here are some examples of topics that could be addressed in this Special Issue:

  1. Deep-learning-based predictors of different neurophysiological diseases and neurological disorders.
  2. Predicting the onset and progression of physical health problems using deep learning models.
  3. Predicting the severity of physical health problems and diseases with deep learning algorithms.
  4. Deep-learning-based prediction of age-related diseases and of developmental disorders in early infancy and childhood.
  5. Deep learning models for predicting the efficacy of medical treatments on physical health.
  6. Identifying physical health risk factors using deep learning models.
  7. Predicting mortality and life expectancy with deep learning algorithms.
  8. Deep-learning-based models to study and promote general well-being.

Dr. Giulio Gabrieli
Dr. Gianluca Esposito
Dr. Andrea Bizzego
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • deep learning
  • physical health
  • psychological health
  • age-related disorders
  • personalized medicine
  • predictive approaches
  • artificial intelligence for healthcare

Published Papers

There is no accepted submissions to this special issue at this moment.
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