Data-Driven Mental Healthcare

Dear Colleagues,

Data-driven approaches have the potential to transform the way we understand, diagnose, treat, and monitor mental health conditions, offering new insights and personalized interventions. This Special Issue aims to explore the exciting developments and challenges in the realm of data-driven mental healthcare, highlighting cutting-edge research, innovative methodologies, and emerging trends in this rapidly evolving field.

Mental health disorders pose a significant global burden, affecting millions of individuals worldwide. However, traditional approaches to mental healthcare often face limitations in terms of accurate diagnosis, individualized treatment plans and goals, predicting prognosis and treatment outcomes, to name a few. The integration of data-driven techniques, including artificial intelligence, machine learning, and big data analytics, offers promising solutions to address these and similar challenges. By harnessing the power of data, researchers and practitioners can gain deeper insights into the complexities of mental health, paving the way for more effective interventions and improved patient outcomes.

One of the key advantages of data-driven mental healthcare lies in its ability to leverage diverse sources of data. Electronic health records, wearable devices, social media platforms, and online communities generate a wealth of data that can provide valuable information about individuals' mental states, behavior patterns, and social interactions. These multidimensional data sources, when analyzed with computational techniques, enable researchers to develop comprehensive models for understanding mental health, identifying risk factors, and predicting mental health outcomes at an individual and population level.

Dr. Ariel Rosenfeld
Guest Editor

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. Information 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 1600 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.

• data-driven mental healthcare
• artificial intelligence
• machine learning
• big data analytics
• diagnosis
• treatment outcomes
• electronic health records
• wearable devices
• social media data
• risk factors
• predictive modeling
• natural language processing
• sentiment analysis
• mobile applications
• remote monitoring
• ethical implications