Recent advances in machine learning (ML) promise far-reaching improvements across medical care, not least within psychiatry. While to date no psychiatric application of ML constitutes standard clinical practice, it seems crucial to get ahead of these...
Supervised machine learning has been increasingly used in psychology and psychiatry research. Machine learning offers an important advantage over traditional statistical analyses: statistical model training in example data to enhance predictions in e...
Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry
May 18, 2020
Bulletin of the World Health Organization
Feb 25, 2020
The application of digital technology to psychiatry research is rapidly leading to new discoveries and capabilities in the field of mobile health. However, the increase in opportunities to passively collect vast amounts of detailed information on stu...
Biological psychiatry. Cognitive neuroscience and neuroimaging
Dec 13, 2019
Data science and digital technologies have the potential to transform diagnostic classification. Digital technologies enable the collection of big data, and advances in machine learning and artificial intelligence enable scalable, rapid, and automate...
The journal of the American Academy of Psychiatry and the Law
Nov 21, 2019
In March 2015, a co-pilot flying Germanwings Flight 9525 deliberately pointed his airplane into a descent, killing himself, five other crew members, and 144 passengers. Subsequent investigation and review teams examined the incident and considered po...
BACKGROUND: Futurists have predicted that new autonomous technologies, embedded with artificial intelligence (AI) and machine learning (ML), will lead to substantial job losses in many sectors disrupting many aspects of healthcare. Mental health appe...
Machine learning methods hold promise for personalized care in psychiatry, demonstrating the potential to tailor treatment decisions and stratify patients into clinically meaningful taxonomies. Subsequently, publication counts applying machine learni...