Computational Psychiatry Research Map (CPSYMAP)
A New Database for Visualizing Research Papers
Bibliographic Data
| ID | 15519187 |
|---|---|
| Authors | Ayaka Kato (0000-0002-6306-6600, The University of Tokyo), Yoshihiko Kunisato (0000-0002-5830-7182, Senshu University), Kentaro Katahira (0000-0002-2018-3938, Nagoya University), Tsukasa Okimura (0000-0001-7795-4337, Keio University), Yuichi Yamashita (0000-0002-2779-8222, National Center of Neurology and Psychiatry, corresponding author) |
| Year | 2020 |
| Volume | 11 |
| Pages | 578706-578706 |
| Publication date | 2020-12-03 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Psychiatry (JOURNAL) |
| Journal identifiers | ISSN: 1664-0640 • E-ISSN: 1664-0640 |
| Publisher | Frontiers Media (PUBLISHER • CH) |
| DOI | 10.3389/fpsyt.2020.578706 |
| PMID | 33343418 |
| OpenAlex | W3107925048 |
| Language | EN |
| Citations received | 1 |
| References cited | 24 |
The field of computational psychiatry is growing in prominence along with recent advances in computational neuroscience, machine learning, and the cumulative scientific understanding of psychiatric disorders. Computational approaches based on cutting-edge technologies and high-dimensional data are expected to provide an understanding of psychiatric disorders with integrating the notions of psychology and neuroscience, and to contribute to clinical practices. However, the multidisciplinary nature of this field seems to limit the development of computational psychiatry studies. Computational psychiatry combines knowledge from neuroscience, psychiatry, and computation; thus, there is an emerging need for a platform to integrate and coordinate these perspectives. In this study, we developed a new database for visualizing research papers as a two-dimensional "map" called the Computational Psychiatry Research Map (CPSYMAP). This map shows the distribution of papers along neuroscientific, psychiatric, and computational dimensions to enable anyone to find niche research and deepen their understanding ofthe field
Cognitive science · Computational model · Computational neuroscience · Data science · Field (mathematics · Interdisciplinarity · Multidisciplinary approach · Neuroinformatics · Psychiatry · Sociology · Computer Science · Functional Brain Connectivity Studies · Machine Learning in Healthcare · Mental Health Research Topics · Neuroscience · Psychology · Artificial Intelligence
| Unique citing works | 1 |
|---|---|
| Citations per year | 0,17 |
| Citation span | 2020 - 2020 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |