AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Child, Preschool

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Predicting high-need high-cost pediatric hospitalized patients in China based on machine learning methods.

Scientific reports
Rapidly increasing healthcare spending globally is significantly driven by high-need, high-cost (HNHC) patients, who account for the top 5% of annual healthcare costs but over half of total expenditures. The programs targeting existing HNHC patients ...

Automated extraction of functional biomarkers of verbal and ambulatory ability from multi-institutional clinical notes using large language models.

Journal of neurodevelopmental disorders
BACKGROUND: Functional biomarkers in neurodevelopmental disorders, such as verbal and ambulatory abilities, are essential for clinical care and research activities. Treatment planning, intervention monitoring, and identifying comorbid conditions in i...

Accuracy of Artificial Intelligence in Making Diagnoses and Treatment Decisions in Pediatric Dentistry.

Pediatric dentistry
To assess the diagnostic and treatment decision-making accuracy of ChatGPT for various dental problems in pediatric patients compared to specialized pediatric dentists. This study included 12 cases, each with an average of three dental problems, re...

Clinical assessment of the criticality index - dynamic, a machine learning prediction model of future care needs in pediatric inpatients.

PloS one
OBJECTIVE: To assess patient characteristics and care factors that are associated with correct and incorrect predictions of future care locations (ICU vs. non-ICU) by the Criticality Index-Dynamic (CI-D), with the goal of enhancing the CI-D.

Machine learning for predicting medical outcomes associated with acute lithium poisoning.

Scientific reports
The use of machine learning algorithms and artificial intelligence in medicine has attracted significant interest due to its ability to aid in predicting medical outcomes. This study aimed to evaluate the effectiveness of the random forest algorithm ...

Machine learning approaches reveal methylation signatures associated with pediatric acute myeloid leukemia recurrence.

Scientific reports
Acute myeloid leukemia (AML) is a severe hematological malignancy characterized by high recurrence rates, especially in pediatric patients, highlighting the need for reliable prognostic markers. This study proposes methylation signatures associated w...

A robot's efficient demonstration cannot reduce 5- to 6-year-old children's over-imitation.

Journal of experimental child psychology
Children tend to imitate inefficient behaviors containing causally irrelevant actions-they over-imitate. Out-group members' efficient demonstration cannot reduce children's over-imitation of in-group members, due to their interpretation of irrelevant...

Machine Learning Models for Predicting Pediatric Hospitalizations Due to Air Pollution and Humidity: A Retrospective Study.

Pediatric pulmonology
BACKGROUND: Exposure to air pollution and meteorological conditions, such as humidity, has been linked to adverse respiratory health outcomes in children. This study aims to develop predictive models for pediatric hospitalizations based on both envir...

Behavior recognition technology based on deep learning used in pediatric behavioral audiometry.

Scientific reports
This study aims to explore the feasibility and accuracy of deep learning-based pediatric behavioral audiometry. The research provides a dedicated pediatric posture detection dataset, which contains a large number of video clips from children's behavi...