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A signature-based machine learning model for distinguishing bipolar disorder and borderline personality disorder
(2018)
Mobile technologies offer new opportunities for prospective, high resolution monitoring of long-term health
conditions. The opportunities seem of particular promise in psychiatry where diagnoses often rely on retrospective
and ...
Experiences of remote mood and activity monitoring in bipolar disorder: a qualitative study
(2017-01)
Mobile technology enables high frequency mood monitoring and automated passive collection of date(e.g.actigraphy) from patients more efficiently and less intrusively than has previously been possible. Such techniques are ...
Characterizing Affective Variability in Bipolar Disorder and Borderline Personality Disorder, and the Effects of Lithium, Using a Generative Model of Affect
(2022-02)
The affective variability of Bipolar Disorder (BD) is thought to qualitatively differ from that of Borderline Personality Disorder (BPD), with changes in affect persisting for longer in BD. However, quantitative studies ...