Latest AI and machine learning research in psychiatry for healthcare professionals.
Mood disorders include all types of depression and bipolar disorder, and mood disorders are sometimes called affective disorders. We will discuss newly developing two issues in affective disorders in children and adolescents. Those are the new diagnostic challenges using neuroimaging techniques in affective disorders and the introduction of disruptive mood dysregulation disorder (DMDD). During the...
Mental disorders are highly prevalent and often remain untreated. Many limitations of conventional face-to-face psychological interventions could potentially be overcome through Internet-based and mobile-based interventions (IMIs). This chapter introduces core features of IMIs, describes areas of application, presents evidence on the efficacy of IMIs as well as potential effect mechanisms, and del...
Sickle cell disease (SCD) is one of the most common monogenic diseases in humans with multiple phenotypic expressions that can manifest as both acute ...
The advances in the Internet and related technologies may lead to changes in professional roles of psychiatrists and psychotherapists. The application...
Locomotion is an important human faculty that affects an individual's life, bringing not only physical and psychosocial implications but also heavy so...
Recently, the interest of industry, government agencies and healthcare professionals in technology for aging people has increased. The challenge is wh...
The authors combined virtual reality technology and social robotics to develop a tutoring system that resembled a small-group arrangement. This tutori...
PURPOSE OF REVIEW: Over the past 10 years, the use of information and communication technologies (ICTs) has increased in regard to the treatment of in...
OBJECTIVE: Develop an approach, One-class-at-a-time, for triaging psychiatric patients using machine learning on textual patient records. Our approach...
BACKGROUND: Social housing may provide an affordable and secure residential environment, but has also been associated with stigma, poor housing condit...
IMPORTANCE: Altered neurodevelopmental trajectories are thought to reflect heterogeneity in the pathophysiologic characteristics of schizophrenia, but...
Machine learning methods are being increasingly applied to physical healthcare. In this article we describe some of the potential benefits, challenges...
BACKGROUND: The variability of responses to plasticity-inducing repetitive transcranial magnetic stimulation (rTMS) challenges its successful applicat...
Past work on relatively small, single-site studies using regional volumetry, and more recently machine learning methods, has shown that widespread str...
Specific biomarker reflecting neurobiological substrates of schizophrenia (SZ) is required for its diagnosis and treatment selection of SZ. Evidence f...
Identifying distinctive subtypes of schizophrenia could ultimately enhance diagnostic and prognostic accuracy. We aimed to uncover neuroanatomical sub...
Genetic risk variants for schizophrenia have been linked to many related clinical and biological phenotypes with the hopes of delineating how individu...