AIMC Topic: Young Adult

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Trauma-predictive brain network connectivity adaptively responds to mild acute stress.

Proceedings of the National Academy of Sciences of the United States of America
Past traumatic experiences shape neural responses to future stress, but the mechanisms underlying this dynamic interaction remain unclear. Here, we assessed how trauma-related brain networks respond to current acute stress in real time. Using a machi...

Skin Microbiome alterations in heroin users revealed by full-length 16S rRNA sequencing.

BMC microbiology
BACKGROUND: Identifying key characteristics of unknown suspects, such as age, height, and drug use, is essential for advancing forensic investigations.

MentalAId: an improved DenseNet model to assist scalable psychosis assessment.

BMC psychiatry
BACKGROUND: The escalating mental health crisis during and post-COVID-19 underscores the urgent need for scalable, timely, cost-effective assessment solutions for general psychotic disorders. Regretfully, traditional symptom-based, one-to-one assessm...

Text-related functionality and dynamics of visual human pre-frontal activations revealed through neural network convergence.

Communications biology
Human prefrontal areas show enhanced activations when individuals are presented with images, under diverse task conditions. However, the functional role of these increased activations remains a deeply debated question. Here we addressed this question...

Predicting Engagement With Conversational Agents in Mental Health Therapy by Examining the Role of Epistemic Trust, Personality, and Fear of Intimacy: Cross-Sectional Web-Based Survey Study.

JMIR human factors
BACKGROUND: The use of conversational agents (CAs) in mental health therapy is gaining traction due to their accessibility, anonymity, and nonjudgmental nature. However, understanding the psychological factors driving preferences for CA-based therapy...

Readiness and Acceptance of Nursing Students Regarding AI-Based Health Care Technology on the Training of Nursing Skills in Saudi Arabia: Cross-Sectional Study.

JMIR nursing
BACKGROUND: The rapid advancements in artificial intelligence (AI) technologies across various sectors, including health care, necessitate the need for a comprehensive understanding of their applications. Specifically, the acceptance and readiness of...

AI-based prediction of depression symptomatology in first-episode psychosis patients: insights from the EUFEST and RAISE-ETP clinical trials.

Psychological medicine
BACKGROUND: Depressive symptoms are highly prevalent in first-episode psychosis (FEP) and worsen clinical outcomes. It is currently difficult to determine which patients will have persistent depressive symptoms based on a clinical assessment. We aime...

Classifying social and physical pain from multimodal physiological signals using machine learning.

Scientific reports
Accurate pain assessment is essential for effective management; however, most studies have focused on differentiating pain from non-pain or estimating pain intensity rather than distinguishing between distinct pain types. We present a machine learnin...

The application and predictive value of the weight-adjusted-waist index in BC prevalence assessment: a comprehensive statistical and machine learning analysis using NHANES data.

BMC cancer
BACKGROUND: Obesity is a known risk factor for breast cancer (BC), but conventional metrics such as body mass index (BMI) may insufficiently capture central adiposity. The weight-adjusted waist index (WWI) has emerged as a potentially superior anthro...

Epigenomic diagnosis and prognosis of Acute Myeloid Leukemia.

Nature communications
Despite the critical role of DNA methylation, clinical implementations harnessing its promise have not been described in acute myeloid leukemia. Utilizing DNA methylation from 3314 leukemia patient samples across 11 harmonized cohorts, we describe th...