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NPP-Digital Psychiatry and Neuroscience
ISSN 2948-1570 · Springer · 58 artikel di indeks
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Artikel Jurnal
Novel TMS-derived metrics enable machine learning classification of major depressive disorder
Abstract No validated biomarker currently exists for early detection or personalized treatment of major depressive disorder (MDD). Transcranial magnetic stimulation (TMS) is widely used in clinical and research settings and holds promise for biomarker discovery. We assessed two novel TMS-derived…
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In their own words: case studies of adolescent smartphone language preceding suicide-related hospitalizations
Abstract Rising adolescent suicide rates underscore an urgent need for better detection of short-term risk in the days and hours leading up to attempts. Passive smartphone sensing of language offers a promising approach, yet its performance during vulnerable periods remains unclear. This case study…
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Artikel Jurnal
Toward actionable biomarkers in psychiatry: a collaborative roadmap for precision clinical trials. An ACNP position paper
Abstract Psychiatric drug development remains constrained by diagnostic heterogeneity, insufficient and inconsistent drug response, high placebo response rates, and the absence of validated biomarkers that can reliably guide patient stratification, trial design, and regulatory decision-making…
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Responsible and innovative AI for mental health care: five priority themes
Abstract Artificial intelligence (AI) has entered psychiatry at scale, yet its clinical impact remains constrained by a sizable gap between technical validation and real-world implementation. The central barriers are no longer computational, but infrastructural: unreliable measurement systems…
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Does ChatGPT need a psychiatrist? Similarities between human psychopathology and errors in large language models
Abstract Two striking phenomena of the human mind encountered in mental healthcare are hallucinations and confabulations; perceiving things that are not there, or filling memory gaps with invented stories. Interestingly, contemporary artificial intelligence systems, such as large language models…
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Characterizing the spiral: potential mechanisms in AI-associated delusions
Abstract AI-associated delusions represent an emerging phenomenon requiring mechanistic understanding. This review, after summarizing key contributions on AI-associated delusions, proposes the "amplification spiral" framework, wherein three empirically observed AI characteristics—linguistic…
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Bouncing back from stress: objective markers of expressive flexibility and resilience in emergency healthcare workers using computer vision
Abstract Healthcare workers (HCWs) in emergency departments face significant mental health risk due to chronic stressors and repeated trauma, yet symptom underreporting and bias in self-reports hinder accurate assessments. Expressive flexibility, the ability to dynamically modulate and recover from…
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Building the foundations for global data banking in digital phenotyping for mental health
Abstract Mental illness is a leading cause of global disability, underscoring the urgent need for scalable, data-driven approaches to early identification and intervention. Passive sensing technologies in mobile and wearable devices enable continuous and unobtrusive measurement of behavioural and…
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Personalized machine learning guided intervention for optimizing lifestyle behaviors in depression: a pilot study
Abstract Personalized data-driven interventions for depression are much needed. Here, we leveraged N-of-1 machine learning (ML) to optimally target behavioral lifestyle interventions for depression. 50 individuals with mild-to-moderate depression enrolled in the single-arm, open-label Personalized…
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Advancing neurotech justice in youth digital mental health: insights from an interdisciplinary and cross-generational workshop
Abstract Researchers and clinicians are increasingly looking to leverage artificial intelligence (AI) and digital tools to improve psychiatric care. Of particular promise is addressing the youth mental health crisis. Yet, the introduction of AI-enabled digital technologies for psychiatric treatment…
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Setting digital psychiatry in motion: towards dynamic digital markers for digital phenotyping
Abstract Digital phenotyping uses data from smartphones and wearables to extract behavioural and biosocial markers of psychopathology in situ. Traditional entropy-based measures capture static system properties that neglect temporal dependencies critical to psychiatric phenomena. We propose a…
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Adherence to ecological momentary assessment studies in children and adolescents with psychopathology: A systematic review with meta-analysis
Abstract Ecological momentary assessment (EMA) is a tool facilitating the repeated collection of real-time data in naturalistic settings that can be applied to clinical research. Despite established methodological strengths, EMA protocols may be burdensome for participants, potentially leading to…
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Launching an independent research laboratory in a digital era: practical lessons for early career investigators
Abstract The transition from trainee to principal investigator represents a major inflection point in an academic research career. While doctoral and postdoctoral training programs provide extensive preparation in experimental design, data analysis, and scientific communication, far less attention…
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A probabilistic deep learning approach for choroid plexus segmentation in autism spectrum disorder
Abstract The choroid plexus serves as the primary barrier between the brain’s blood and cerebrospinal fluid and mediates neuroimmune function. A subset of individuals with autism spectrum disorder (ASD) may exhibit morphological alterations of the choroid plexus. However, to power larger population…
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The impact of neuroscience education therapy, behavioral economics, and digital navigators on patient migraine treatment adherence to a mobile health application: a prospective pilot randomized controlled trial
Abstract Mobile health (mHealth) tools can be used to deliver nonpharmacologic therapies to patients with migraine. However, mHealth studies often report poor treatment adherence. Neuroscience Education Therapy (NET), behavioral economics, and Digital Navigators have the potential to increase…
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Artikel Jurnal
EEG-based brain connectivity and sentiment analysis from smartphone social communication: insights into remitted major depressive disorder among adolescents
Abstract Although prior research has identified abnormal brain connectivity in remitted depressed adolescents, there is limited work associating these alterations with real-time affective dynamics, which may shed insight about specific biological markers that contribute to depression recurrence…