AIMC Topic: Young Adult

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Identifying high-dose opioid prescription risks using machine learning: A focus on sociodemographic characteristics.

Journal of opioid management
OBJECTIVE: The objective of this study was to leverage machine learning techniques to analyze administrative claims and socioeconomic data, with the aim of identifying and interpreting the risk factors associated with high-dose opioid prescribing.

Reliability of Emotion Analysis from Human Facial Expressions Using Multi-task Cascaded Convolutional Neural Networks.

The journal of medical investigation : JMI
Life support robots in care settings must be able to read a person's emotions from facial expressions to achieve empathic communication. This study aims to determine the degree of agreement between Multi-task Cascaded Convolutional Neural Networks (M...

Using the Minnesota Multiphasic Personality Inventory-2 restructured form to predict functioning after treatment for borderline personality disorder: A machine learning approach.

Psychological assessment
Insight into predictors of functioning after treatment for borderline personality disorder (BPD) is limited, despite growing recognition that more focus on other aspects of recovery, especially psychosocial functioning, is warranted. The present stud...

Can the Use of Artificial Intelligence-Generated Content Bridge the Cancer Knowledge Gap? A Longitudinal Study With Health Self-Efficacy as a Mediator and Educational Level as a Moderator.

Cancer control : journal of the Moffitt Cancer Center
OBJECTIVES: The cancer knowledge gap represents a significant disparity in awareness and understanding of cancer-related information across different demographic groups. Leveraging Artificial Intelligence-Generated Content (AIGC) offers a promising a...

Unmasking the Dark Triad: A Data Fusion Machine Learning Approach to Characterize the Neural Bases of Narcissistic, Machiavellian and Psychopathic Traits.

The European journal of neuroscience
The Dark Triad (DT), encompassing narcissism, Machiavellianism and psychopathy traits, poses significant societal challenges. Understanding the neural underpinnings of these traits is crucial for developing effective interventions and preventive stra...

Using machine learning to predict patients with polycystic ovary disease in Chinese women.

Taiwanese journal of obstetrics & gynecology
OBJECTIVE: With an estimated global frequency ranging from5 % to 21 %, polycystic ovary syndrome (PCOS) is one of the most prevalent hormonal disorders. There are many factors found to be related to PCOS. However, most of these researches used tradit...

A Soft Robotic Sleeve for Physiotherapy: Improving Elbow Rehabilitation in Baseball Pitchers.

Physiotherapy research international : the journal for researchers and clinicians in physical therapy
BACKGROUND AND PURPOSE: Throwing a baseball involves intense exposure of the arm to high speeds and powerful forces, which contributes to an increasing prevalence of arm injuries among athletes. Traditional rigid exoskeletons and rehabilitation equip...

Predicting Antidepressant Treatment Response From Cortical Structure on MRI: A Mega-Analysis From the ENIGMA-MDD Working Group.

Human brain mapping
Accurately predicting individual antidepressant treatment response could expedite the lengthy trial-and-error process of finding an effective treatment for major depressive disorder (MDD). We tested and compared machine learning-based methods that pr...

Diagnosis of Schizophrenia and Its Subtypes Using MRI and Machine Learning.

Brain and behavior
PURPOSE: The neurobiological heterogeneity present in schizophrenia remains poorly understood. This likely contributes to the limited success of existing treatments and the observed variability in treatment responses. Our objective was to employ magn...

World-making for a future with sentient AI.

The British journal of social psychology
The ways people imagine possible futures with artificial intelligence (AI) affects future world-making-how the future is produced through cultural propagation, design, engineering, policy, and social interaction-yet there has been little empirical st...