Pediatrics

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

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Dynamic multilayer growth: Parallel vs. sequential approaches.

The decision of when to add a new hidden unit or layer is a fundamental challenge for constructive a...

Multimodal deep learning-based drought monitoring research for winter wheat during critical growth stages.

Wheat is a major grain crop in China, accounting for one-fifth of the national grain production. Dro...

Establishment and Verification of an Artificial Intelligence Prediction Model for Children With Sepsis.

BACKGROUND: Early identification of high-risk groups of children with sepsis is beneficial to reduce...

The Saudi Community View of the Use of Artificial Intelligence in Health Care.

OBJECTIVES: Artificial intelligence (AI) holds the promise to revolutionize the field of medicine an...

Magnetic Microrobot Swarms with Polymeric Hands Catching Bacteria and Microplastics in Water.

The forefront of micro- and nanorobot research involves the development of smart swimming micromachi...

GNN-based structural information to improve DNN-based basal ganglia segmentation in children following early brain lesion.

Analyzing the basal ganglia following an early brain lesion is crucial due to their noteworthy role ...

Application of machine learning approaches for predicting hemophilia A severity.

BACKGROUND: Hemophilia A (HA) is an X-linked congenital bleeding disorder, which leads to deficiency...

Predicting humoral responses to primary and booster SARS-CoV-2 mRNA vaccination in people living with HIV: a machine learning approach.

BACKGROUND: SARS-CoV-2 mRNA vaccines are highly immunogenic in people living with HIV (PLWH) on effe...

Model-Informed Precision Dosing Using Machine Learning for Levothyroxine in General Practice: Development, Validation and Clinical Simulation Trial.

Levothyroxine is one of the most prescribed drugs in the western world. Dosing is challenging due to...

The role and future prospects of artificial intelligence algorithms in peptide drug development.

Peptide medications have been more well-known in recent years due to their many benefits, including ...

Development and comparison of machine learning models for in-vitro drug permeation prediction from microneedle patch.

The field of machine learning (ML) is advancing to a larger extent and finding its applications acro...

Enhancing Fetal Electrocardiogram Signal Extraction Accuracy through a CycleGAN Utilizing Combined CNN-BiLSTM Architecture.

The fetal electrocardiogram (FECG) records changes in the graph of fetal cardiac action potential du...

Automated machine learning model for fundus image classification by health-care professionals with no coding experience.

To assess the feasibility of code-free deep learning (CFDL) platforms in the prediction of binary ou...

HFSCCD: A Hybrid Neural Network for Fetal Standard Cardiac Cycle Detection in Ultrasound Videos.

In the fetal cardiac ultrasound examination, standard cardiac cycle (SCC) recognition is the essenti...

Intensive longitudinal assessment following index trauma to predict development of PTSD using machine learning.

There are significant challenges to identifying which individuals require intervention following exp...

Metrisor: A novel diagnostic method for metritis detection in cattle based on machine learning and sensors.

The Metrisor device has been developed using gas sensors for rapid, highly accurate and effective di...

A comprehensive assessment of machine learning algorithms for enhanced characterization and prediction in orodispersible film development.

Orodispersible films (ODFs) have emerged as innovative pharmaceutical dosage forms, offering patient...

Image segmentation of impacted mesiodens using deep learning.

This study aimed to evaluate the performance of deep learning algorithms for the classification and ...

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