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 284
Special Issue Editors
Interests: machine learning; deep learning; psychology; neurophysiology
Interests: social neuroscience; clinical psychology
Special Issues, Collections and Topics in MDPI journals
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:
- Deep-learning-based predictors of different neurophysiological diseases and neurological disorders.
- Predicting the onset and progression of physical health problems using deep learning models.
- Predicting the severity of physical health problems and diseases with deep learning algorithms.
- Deep-learning-based prediction of age-related diseases and of developmental disorders in early infancy and childhood.
- Deep learning models for predicting the efficacy of medical treatments on physical health.
- Identifying physical health risk factors using deep learning models.
- Predicting mortality and life expectancy with deep learning algorithms.
- 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
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Keywords
- deep learning
- physical health
- psychological health
- age-related disorders
- personalized medicine
- predictive approaches
- artificial intelligence for healthcare
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