Deep neural networks in psychiatry
Abstract Machine and deep learning methods, today's core of artificial intelligence, have
been applied with increasing success and impact in many commercial and research …
been applied with increasing success and impact in many commercial and research …
Smartphone sensing methods for studying behavior in everyday life
Highlights•Smartphone Sensing Methods (SSMs) permit continuous and real-time
behavioral observation in the context of people's daily lives.•SSMs provide objective …
behavioral observation in the context of people's daily lives.•SSMs provide objective …
Tracking depression dynamics in college students using mobile phone and wearable sensing
There are rising rates of depression on college campuses. Mental health services on our
campuses are working at full stretch. In response researchers have proposed using mobile …
campuses are working at full stretch. In response researchers have proposed using mobile …
[HTML][HTML] Digital phenotyping for monitoring mental disorders: systematic review
P Bufano, M Laurino, S Said, A Tognetti… - Journal of Medical …, 2023 - jmir.org
Background The COVID-19 pandemic has increased the impact and spread of mental
illness and made health services difficult to access; therefore, there is a need for remote …
illness and made health services difficult to access; therefore, there is a need for remote …
[HTML][HTML] Correlations between objective behavioral features collected from mobile and wearable devices and depressive mood symptoms in patients with affective …
Background: Several studies have recently reported on the correlation between objective
behavioral features collected via mobile and wearable devices and depressive mood …
behavioral features collected via mobile and wearable devices and depressive mood …
Deepmood: Forecasting depressed mood based on self-reported histories via recurrent neural networks
Depression is a prevailing issue and is an increasing problem in many people's lives.
Without observable diagnostic criteria, the signs of depression may go unnoticed, resulting …
Without observable diagnostic criteria, the signs of depression may go unnoticed, resulting …
Passive sensing of prediction of moment-to-moment depressed mood among undergraduates with clinical levels of depression sample using smartphones
NC Jacobson, YJ Chung - Sensors, 2020 - mdpi.com
Prior research has recently shown that passively collected sensor data collected within the
contexts of persons daily lives via smartphones and wearable sensors can distinguish those …
contexts of persons daily lives via smartphones and wearable sensors can distinguish those …
[HTML][HTML] Mobile phone and wearable sensor-based mHealth approaches for psychiatric disorders and symptoms: systematic review
J Seppälä, I De Vita, T Jämsä, J Miettunen… - JMIR mental …, 2019 - mental.jmir.org
Background: Mobile Therapeutic Attention for Patients with Treatment-Resistant
Schizophrenia (m-RESIST) is an EU Horizon 2020-funded project aimed at designing and …
Schizophrenia (m-RESIST) is an EU Horizon 2020-funded project aimed at designing and …
[HTML][HTML] Ethics and law in research on algorithmic and data-driven technology in mental health care: scoping review
P Gooding, T Kariotis - JMIR Mental Health, 2021 - mental.jmir.org
Background Uncertainty surrounds the ethical and legal implications of algorithmic and data-
driven technologies in the mental health context, including technologies characterized as …
driven technologies in the mental health context, including technologies characterized as …
Predicting symptom trajectories of schizophrenia using mobile sensing
Continuously monitoring schizophrenia patients' psychiatric symptoms is crucial for in-time
intervention and treatment adjustment. The Brief Psychiatric Rating Scale (BPRS) is a survey …
intervention and treatment adjustment. The Brief Psychiatric Rating Scale (BPRS) is a survey …