AIMC Topic: Adolescent

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Evaluation of ChatGPT-4 responses on physical activity guidance in children with cystic fibrosis: reliability, quality, and readability.

European journal of pediatrics
UNLABELLED: ChatGPT-4 is a widely used large language model that provides instant answers to a variety of health-related questions in different medical fields. This study aims to evaluate the reliability, quality, accuracy, and readability of ChatGPT...

Distinct electroencephalogram microstate in patients with methamphetamine use disorder and obsessive-compulsive disorder.

Journal of affective disorders
BACKGROUND: Electroencephalogram (EEG) microstates reflect momentary localized brain activity and may indicate spontaneous fluctuations within large-scale neural networks. Methamphetamine use disorder (MUD) and obsessive-compulsive disorder (OCD) exh...

Multifactorial Biomarkers for "Talk and Deteriorate" after Head Trauma Identified Using Machine Learning.

Neurologia medico-chirurgica
Talk and Deteriorate refers to a clinical course where a patient is able to speak immediately after a traumatic brain injury but subsequently deteriorates in consciousness. Talk and Deteriorate outcomes are poor, and reliable prediction may help impr...

Predicting outcomes in pediatric patients with acute kidney injury: a retrospective single-center cohort study using machine learning models.

BMC medical informatics and decision making
OBJECTIVE: To develop and evaluate machine learning models combined with survival analysis for predicting 7-, 14-, and 28-day mortality in critically ill children with acute kidney injury (AKI), identifying key predictors to guide risk stratification...

Detecting mind wandering via EEG and facial video features.

Behavior research methods
PURPOSE: Mind wandering (MW), a common cognitive phenomenon marked by a shift of attention away from the task at hand, poses significant challenges in online educational settings. This study aims to advance MW detection by developing a classification...

Evaluating the readability and quality of AI-generated scoliosis education materials: a comparative analysis of five language models.

Scientific reports
The complexity of scoliosis-related terminology and treatment options often hinders patients and caregivers from understanding their choices, making it difficult to make informed decisions. As a result, many patients seek guidance from artificial int...

Clinical, biochemical, and molecular characterization of a cohort of Egyptian patients with Sanfilippo B syndrome (MPS IIIB): Bayesian Gaussian mixture model.

Molecular biology reports
BACKGROUND: Lysosomal storage diseases (LSDs) are a group of genetically heterogeneous inherited metabolic disorders that affect the functions of the lysosomes in different human tissues. Mucopolysaccharidosis IIIB (MPS IIIB), Sanfilippo B syndrome, ...

Performance of several large language models when answering common patient questions about type 1 diabetes in children: accuracy, comprehensibility and practicality.

BMC pediatrics
BACKGROUND: The use of large language models (LLMs) in healthcare has expanded significantly with advances in natural language processing. Models, such as ChatGPT and Google Gemini, are increasingly used to generate human-like responses to questions,...

SHAP-enhanced machine learning identifies modifiable obesity predictors across adolescent weight groups: A 2021 YRBSS analysis.

PloS one
BACKGROUND: The growing prevalence of obesity in adolescents around the world poses a major threat to public health. This research uses machine learning models to examine the main causes of obesity, in contrast to standard information that typically ...

From objective grouping to fuzzy reference intervals: A standardized machine learning approach for thyroid function tests.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND: Accurate interpretation of thyroid function tests (TFTs) requires reliable reference intervals (RIs). Indirect methods based on retrospective laboratory data are increasingly used, but current strategies face major limitations, including ...