[HTML][HTML] Virtual reality for supporting the treatment of depression and anxiety: scoping review
Background Mental health conditions pose a major challenge to health care providers and
society at large. The World Health Organization predicts that by 2030, mental health …
society at large. The World Health Organization predicts that by 2030, mental health …
[HTML][HTML] A review of challenges and opportunities in machine learning for health
Modern electronic health records (EHRs) provide data to answer clinically meaningful
questions. The growing data in EHRs makes healthcare ripe for the use of machine learning …
questions. The growing data in EHRs makes healthcare ripe for the use of machine learning …
Research domain criteria (RDoC): progress and potential
BN Cuthbert - Current Directions in Psychological Science, 2022 - journals.sagepub.com
The National Institute of Mental Health (NIMH) addressed in its 2008 Strategic Plan an
emerging concern that the current diagnostic system was hampering translational research …
emerging concern that the current diagnostic system was hampering translational research …
Measuring, predicting, and tracking change in psychotherapy
This chapter addresses fundamental issues of change in psychotherapy: how to measure,
monitor, predict change, and provide feedback on treatment outcome. The chapter starts …
monitor, predict change, and provide feedback on treatment outcome. The chapter starts …
Using language processing and speech analysis for the identification of psychosis and other disorders
CM Corcoran, GA Cecchi - Biological Psychiatry: Cognitive Neuroscience …, 2020 - Elsevier
Increasingly, data-driven methods have been implemented to understand psychopathology.
Language is the main source of information in psychiatry and represents “big data” at the …
Language is the main source of information in psychiatry and represents “big data” at the …
A data-driven framework for mapping domains of human neurobiology
Functional neuroimaging has been a mainstay of human neuroscience for the past 25 years.
Interpretation of functional magnetic resonance imaging (fMRI) data has often occurred …
Interpretation of functional magnetic resonance imaging (fMRI) data has often occurred …
Natural language processing with machine learning methods to analyze unstructured patient-reported outcomes derived from electronic health records: A systematic …
Objective Natural language processing (NLP) combined with machine learning (ML)
techniques are increasingly used to process unstructured/free-text patient-reported outcome …
techniques are increasingly used to process unstructured/free-text patient-reported outcome …
Reattribution to mind-brain processes and recovery from chronic back pain: a secondary analysis of a randomized clinical trial
Importance In primary chronic back pain (CBP), the belief that pain indicates tissue damage
is both inaccurate and unhelpful. Reattributing pain to mind or brain processes may support …
is both inaccurate and unhelpful. Reattributing pain to mind or brain processes may support …
Recommended practices and ethical considerations for natural language processing‐assisted observational research: a scoping review
An increasing number of studies have reported using natural language processing (NLP) to
assist observational research by extracting clinical information from electronic health records …
assist observational research by extracting clinical information from electronic health records …
Innovation on machine learning in healthcare services—An introduction
P Pattnayak, AR Panda - Technical Advancements of Machine Learning in …, 2021 - Springer
The healthcare offerings in evolved and developing international locations are seriously
important. The use of machine gaining knowledge of strategies in healthcare enterprise has …
important. The use of machine gaining knowledge of strategies in healthcare enterprise has …