Pediatrics

Latest AI and machine learning research in pediatrics for healthcare professionals.

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Modeling the relationship between maternal health and infant behavioral characteristics based on machine learning.

This study investigates the impact of maternal health on infant development by developing a mathemat...

A future of AI-driven personalized care for people with multiple sclerosis.

Multiple sclerosis (MS) is a devastating immune-mediated disorder of the central nervous system resu...

Applications of artificial intelligence for adolescent idiopathic scoliosis: mapping the evidence.

PURPOSE: Adolescent idiopathic scoliosis (AIS) is a common spinal deformity with varying progression...

Beyond hand-crafted features for pretherapeutic molecular status identification of pediatric low-grade gliomas.

The use of targeted agents in the treatment of pediatric low-grade gliomas (pLGGs) relies on the det...

AI-based derivation of atrial fibrillation phenotypes in the general and critical care populations.

BACKGROUND: Atrial fibrillation (AF) is the most common heart arrhythmia worldwide and is linked to ...

Distinguishing neonatal culture-negative sepsis from rule-out sepsis with artificial intelligence-derived graphs.

Novel artificial intelligence methods can aide in identification of cases of conditions using only u...

The Artificial Intelligence-Powered New Era in Pharmaceutical Research and Development: A Review.

Currently, artificial intelligence (AI), machine learning (ML), and deep learning (DL) are gaining i...

Early sepsis mortality prediction model based on interpretable machine learning approach: development and validation study.

Sepsis triggers a harmful immune response due to infection, causing high mortality. Predicting sepsi...

Predicting ultrasound wave stimulated bone growth in bioinspired scaffolds using machine learning.

For conditions like osteoporosis, changes in bone pore geometry even when porosity is constant have ...

Using machine learning to explore the predictors of life satisfaction trajectories in older adults.

Life satisfaction is vital for older adults' well-being, impacting various life aspects. It is dynam...

Artificial intelligence and myocarditis-a systematic review of current applications.

Myocarditis, marked by heart muscle inflammation, poses significant clinical challenges. This study,...

Revolutionizing adjuvant development: harnessing AI for next-generation cancer vaccines.

With the COVID-19 pandemic, the importance of vaccines has been widely recognized and has led to inc...

Predicting the trajectory of non-suicidal self-injury among adolescents.

BACKGROUND: Non-suicidal self-injury (NSSI) is common among adolescents receiving inpatient psychiat...

Development and validation of a machine learning-based, point-of-care risk calculator for post-ERCP pancreatitis and prophylaxis selection.

BACKGROUND AND AIMS: A robust model of post-ERCP pancreatitis (PEP) risk is not currently available....

Age-stratified predictions of suicide attempts using machine learning in middle and late adolescence.

BACKGROUND: Prevalence of suicidal behaviour increases rapidly in middle to late adolescence. Predic...

Capability of multimodal large language models to interpret pediatric radiological images.

BACKGROUND: There is a dearth of artificial intelligence (AI) development and research dedicated to ...

Artificial intelligence reveals the predictions of hematological indexes in children with acute leukemia.

Childhood leukemia is a prevalent form of pediatric cancer, with acute lymphoblastic leukemia (ALL) ...

Development of Automated Triggers in Ambulatory Settings in Brazil: Protocol for a Machine Learning-Based Design Thinking Study.

BACKGROUND: The use of technologies has had a significant impact on patient safety and the quality o...

Being diagnosed with a rhabdomyosarcoma in the era of artificial intelligence: Whom can we trust?

In the era of big data, young patients may be overwhelmed by artificial intelligence-based tools, li...

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