Pediatrics

Update to improve reproducibility and interpretability: A response to "Machine Learning for Tumor Growth Inhibition".

Design of Automated Deep Learning-Based Fusion Model for Copy-Move Image Forgery Detection.

Due to the exponential growth of high-quality fake photos on social media and the Internet, it is cr...

Research on the Development of Digital Creative Sports Industry Based on Deep Learning.

The core of the digital entrepreneurial sports culture creative industry lies in innovation, which e...

The Design of Adolescents' Physical Health Prediction System Based on Deep Reinforcement Learning.

According to the general recognition in the first half of the last century, hypertension was not con...

Machine learning-informed and synthetic biology-enabled semi-continuous algal cultivation to unleash renewable fuel productivity.

Algal biofuel is regarded as one of the ultimate solutions for renewable energy, but its commerciali...

Developing machine learning models for prediction of mortality in the medical intensive care unit.

BACKGROUND AND OBJECTIVE: Alert of patient deterioration is essential for prompt medical interventio...

Embedded ethics: a proposal for integrating ethics into the development of medical AI.

The emergence of ethical concerns surrounding artificial intelligence (AI) has led to an explosion o...

Development and validation of a machine learning algorithm-based risk prediction model of pressure injury in the intensive care unit.

The study aimed to establish a machine learning-based scoring nomogram for early recognition of like...

Medicolite-Machine Learning-Based Patient Care Model.

This paper discusses the machine learning effect on healthcare and the development of an application...

External validation of deep learning-based bone-age software: a preliminary study with real world data.

Artificial intelligence (AI) is increasingly being used in bone-age (BA) assessment due to its compl...

Development of new computational machine learning models for longitudinal dispersion coefficient determination: case study of natural streams, United States.

Natural streams longitudinal dispersion coefficient (Kx) is an essential indicator for pollutants tr...

Denoising of pediatric low dose abdominal CT using deep learning based algorithm.

OBJECTIVES: To evaluate standard dose-like computed tomography (CT) images generated by a deep learn...

Assessment of Skin Toxicity in an in Vitro Reconstituted Human Epidermis Model Using Deep Learning.

Skin toxicity is a common safety concern associated with drugs that inhibit epidermal growth factor ...

Forensic bone age estimation of adolescent pelvis X-rays based on two-stage convolutional neural network.

In the forensic estimation of bone age, the pelvis is important for identifying the bone age of teen...

Harnessing Artificial Intelligence to assess the impact of nonpharmaceutical interventions on the second wave of the Coronavirus Disease 2019 pandemic across the world.

In the present paper, we aimed to determine the influence of various non-pharmaceutical intervention...

DeLTA 2.0: A deep learning pipeline for quantifying single-cell spatial and temporal dynamics.

Improvements in microscopy software and hardware have dramatically increased the pace of image acqui...

Segmenting pediatric optic pathway gliomas from MRI using deep learning.

Optic pathway gliomas are low-grade neoplastic lesions that account for approximately 3-5% of brain ...

Modeling risk of Sclerotinia sclerotiorum-induced disease development on canola and dry bean using machine learning algorithms.

Diseases caused by the fungus Sclerotinia sclerotiorum are managed mainly through fungicide applicat...

Evaluation of Maturation in Preterm Infants Through an Ensemble Machine Learning Algorithm Using Physiological Signals.

This study was designed to test if heart rate variability (HRV) data from preterm and full-term infa...

Ethical Considerations Related to Using Machine Learning-Based Prediction of Mortality in the Pediatric Intensive Care Unit.

Deep Learning Neural Modelling as a Precise Method in the Assessment of the Chronological Age of Children and Adolescents Using Tooth and Bone Parameters.

Dental age is one of the most reliable methods for determining a patient's age. The timing of teethi...