AIMC Topic: Mental Health Services

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Leveraging Novel Technologies and Artificial Intelligence to Advance Practice-Oriented Research.

Administration and policy in mental health
Mental health services are experiencing notable transformations as innovative technologies and artificial intelligence (AI) are increasingly utilized in a growing number of studies and services.These cutting-edge technologies carry the promise of sub...

Artificial intelligence is set to transform mental health services.

CNS spectrums
The current development in the field of artificial intelligence and its applications has advantages and disadvantages in the digital age that we now live in. The state of the use of AI for mental health has to be assessed by stakeholders, which inclu...

Can natural language processing models extract and classify instances of interpersonal violence in mental healthcare electronic records: an applied evaluative study.

BMJ open
OBJECTIVE: This paper evaluates the application of a natural language processing (NLP) model for extracting clinical text referring to interpersonal violence using electronic health records (EHRs) from a large mental healthcare provider.

Predicting Future Service Use in Dutch Mental Healthcare: A Machine Learning Approach.

Administration and policy in mental health
A mental healthcare system in which the scarce resources are equitably and efficiently allocated, benefits from a predictive model about expected service use. The skewness in service use is a challenge for such models. In this study, we applied a mac...

Approaches to assessing the impact of robotics in geriatric mental health care: a scoping review.

International review of psychiatry (Abingdon, England)
The goals of this scoping literature review are to (1) aggregate the current research involving socially assistive robots in the setting of geriatric psychiatry and (2) examine the outcome measures used in these studies and determine where the gaps a...

A natural language processing approach for identifying temporal disease onset information from mental healthcare text.

Scientific reports
Receiving timely and appropriate treatment is crucial for better health outcomes, and research on the contribution of specific variables is essential. In the mental health domain, an important research variable is the date of psychosis symptom onset,...

Predicting self-harm within six months after initial presentation to youth mental health services: A machine learning study.

PloS one
BACKGROUND: A priority for health services is to reduce self-harm in young people. Predicting self-harm is challenging due to their rarity and complexity, however this does not preclude the utility of prediction models to improve decision-making rega...

Using de-identified electronic health records to research mental health supported housing services: A feasibility study.

PloS one
BACKGROUND: Mental health supported housing services are a key component in the rehabilitation of people with severe and complex needs. They are implemented widely in the UK and other deinstitutionalised countries but there have been few empirical st...