Psychiatry

Comparative oncology of male and female breast cancer: diagnostic paradigms and machine learning approaches in treatment.

Breast cancer is associated mostly with women; however, breast cancer also appears in men, which dictates the need to know about gender-specific differences in the pathology and treatment. Male breast cancer constitutes less than 1 % of all cases and is usually diagnosed when the patient is older, with bigger tumors and at later stages than breast cancer in women. The most widespread subtype in bo...

Influences of adverse childhood experiences and weekly pregnancy stress on postpartum mental health symptoms: a machine learning examination.

PURPOSE: The goal of this study was to understand how the timing, level, and fluctuation of pregnancy stress affected women's postpartum mental health while also considering their experiences of early life stress (adverse childhood events; ACEs). We hypothesized that overall stress level, as well as stress during particular pregnancy weeks, would influence postpartum mental health. We further hypo...

Fear and Prompting: AI, Originary Technicity, and Colonialism.

This paper examines psychoanalysts' affective and defensive responses to artificial intelligence (AI) through the lens of originary technicity, the ph...

Psychosocial Resources and Constraints: Distinct Pathways to Positive and Negative Self-Perceptions of Aging in Diverse Older Adults.

OBJECTIVES: Self-perceptions of aging (SPA) predict behavioral health outcomes in later life, yet whether positive and negative attitudes arise from d...

Prenatal serotonin reuptake inhibitor exposure and maternal depression symptoms are associated with altered fetal brain and placental development.

Maternal mental health is associated with fetal neurodevelopment. Identifying effective treatments for maternal psychiatric conditions is a public hea...

Digital phenotyping for predicting relapse in psychiatric disorders: a systematic review of passive sensing approaches.

BACKGROUND: Digital phenotyping - the moment-by-moment quantification of individual-level human behavior using data from personal digital devices - of...

Diagnostic accuracy of machine learning approaches for suicide‑related outcomes: a meta‑analysis.

OBJECTIVE: This diagnostic test accuracy meta-analysis aimed to provide clinically interpretable estimates (sensitivity, specificity, likelihood ratio...

Are Psychiatry Faculty Prepared to Guide AI Use? A National Survey.

OBJECTIVE: To assess psychiatry faculty knowledge, use, and perceptions of artificial intelligence (AI) in undergraduate medical education (UME) and g...

Identifying factors influencing acceptance of artificial intelligence among general practitioners in Danish general practice: a cross-sectional web-based survey study.

BACKGROUND: Despite rapid advances in artificial intelligence (AI), its adoption in Danish general practice remains limited and decentralized, relying...

Auditory brainstem response abnormalities in autism spectrum disorder: A deep learning approach to characterize time-frequency signatures.

BACKGROUND: While Auditory Brainstem Response (ABR) provides a non-invasive window into auditory brainstem function, prior studies of ASD have primari...

Childhood environment clusters reveal heterogeneous associations between large-scale brain networks and youth mental health symptoms.

BACKGROUND: Youth mental health and brain development are profoundly shaped by highly heterogeneous childhood environments. However, research often op...

Barriers and Facilitators to Patient Acceptance of Artificial Intelligence in Health Care: Systematic Review.

BACKGROUND: Artificial intelligence (AI) in the domain of health care is increasing in prominence. Acceptance is an indispensable prerequisite for the...

Alignment of Lived Experience Questions with the Medical Literature in Bipolar Disorder: A Topic Modelling Approach: Adéquation entre les questions relatives à l'expérience vécue et la littérature médicale concernant le trouble bipolaire : Une approche de modélisation de sujets.

ObjectiveThe priorities of people with mental health challenges should be reflected in the research conducted on their behalf. Quantifying alignment o...

A Guide to Constructing Indigenous Statistical Spaces for Prevention Science Research.

Artificial intelligence (AI)-powered computational methods, such as machine learning and natural language processing, are increasingly applied in deat...

Advances in the Identification and Agreement About Meta-Therapy for Voice Disorders: A Methodological Paper.

BACKGROUND: Meta-therapy (MT) is a powerful dialogue-based element of voice therapy that scaffolds patients' cognitive models of treatment. MT dialogu...

Communication-Based Teaching on Childhood Obesity and the Planetary Health Diet in Medical Education: Proof-of-Concept Study Comparing 4 Information Sources.

BACKGROUND: Childhood obesity constitutes a complex medical and psychosocial challenge that requires both nutritional knowledge and sensitive, relatio...

Cognitive Function Assessment Using a Virtual Reality Serious Game System in Patients With Stable Schizophrenia: Prospective Cohort Study.

BACKGROUND: Cognitive impairment is a core and enduring deficit in schizophrenia, severely affecting social functioning and quality of life. Tradition...

Spatial concordance metrics and related risk factors of brain-peripheral barrier axes: unveiling distinct concordance patterns for mental and neurological axes.

Numerous studies have documented bidirectional interactions between the central nervous system and barrier organs (skin, gut, and lung). While genome-...

Machine learning and SHAP interpretation to identify high-level compassion fatigue among operating room nurses: a multicenter cross-sectional study.

BACKGROUND: Operating room nurses (ORNs) are at high risk for compassion fatigue (CF), which significantly impairs individuals' well-being, undermines...

Identifying pre-treatment risk factors for cancer-related cognitive decline in patients with breast cancer.

PURPOSE: To explore pre-treatment risk factors for cognitive decline in patients with breast cancer using a machine learning approach applied to a com...