AIMC Topic: Young Adult

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Data-augmented machine learning for personalized carbohydrate-protein supplement recommendation for endurance.

Scientific reports
Carbohydrate-protein supplementation often improves endurance performance. However, effectiveness varies significantly among individuals due to unique personal characteristics. This study aimed to develop a predictive machine learning framework for p...

Evaluation of VITA shade-based tooth color categories using deep learning.

Scientific reports
With the increasing interest in dental aesthetics, more patients are seeking tooth shade evaluations and whitening treatments. However, traditional methods of visually assessing tooth color with a commercial shade guide are often subjective, emphasiz...

Exploring Body Image Awareness With a Large Language Model-Based Conversational Agent: Qualitative Study With Young Adults.

Journal of medical Internet research
BACKGROUND: Body image plays a crucial role in both physical and mental health, influencing self-esteem, eating behaviors, and psychological well-being. Young adults are particularly vulnerable to body dissatisfaction, defined as negative thoughts or...

Application of Narrative and AI-Assisted Follow-Up After Voluntary Medical Male Circumcision: Multicenter, Double-Blind, Prospective, Randomized Controlled Trial.

Journal of medical Internet research
BACKGROUND: Postoperative anxiety following voluntary medical male circumcision (VMMC) poses a significant health challenge, with limited telemedicine access and inadequate communication compromising recovery and adherence. Narrative-based interventi...

Electroencephalography source-space functional connectivity reveals frequency-specific brain network dysfunctions in obsessive-compulsive disorder.

Progress in neuro-psychopharmacology & biological psychiatry
BACKGROUND: Obsessive-compulsive disorder (OCD) is characterized by disruptions in large-scale brain networks. However, the role of high-frequency neural synchrony in these abnormalities remains unclear. Elucidating frequency-specific alterations may...

The need for speed: using nystagmus velocity profiles and machine learning models to separate canalithiasis BPV from its mimics.

Journal of neurology
PURPOSE: Separating BPV from other positional nystagmus types can be challenging. We examined the utility of nystagmus slow-phase velocity (SPV) profiles when seeking to separate canalithiasis benign positional vertigo (BPV) from its mimics.

Decoding brain structure-function dynamics in health and in psychosis via an autoencoder.

Scientific reports
Understanding the intricate relationship between brain structure and function is a cornerstone challenge in neuroscience, critical for deciphering the mechanisms that underlie healthy and pathological brain function. In this work, we present a compre...

Graph-theoretical analysis of EEG-based functional connectivity during emotional experience in virtual reality for emotion recognition.

Scientific reports
Virtual reality (VR) technologies can induce realistic emotions in controlled experimental settings, offering unprecedented opportunities to study how the human brain processes emotions under real-world conditions. The integration of VR experiences w...

Multimodal prediction of psychotic-like experiences using elastic net modeling: external validation in a clinical sample.

Psychological medicine
BACKGROUND: Psychotic-like experiences (PLEs) are considered a subclinical component of psychosis continuum. Studies indicate that PLEs arise from multimodal factors, yet research comprehensively examining these factors together remains scarce. Using...

Applied machine learning for nociceptive pain detection using EEG spectral features.

Biomedical physics & engineering express
. This study explores a more reliable method for measuring nociceptive pain induced by laser stimuli from electroencephalography (EEG) signals, addressing the limitations of fixed pain scales by incorporating inter-individual variability in subjectiv...