Pediatrics

External validation of machine learning models including newborn metabolomic markers for postnatal gestational age estimation in East and South-East Asian infants.

 Postnatal gestational age (GA) algorithms derived from newborn metabolic profiles have emerged as a novel method of acquiring population-level preterm birth estimates in low resource settings. To date, model development and validation have been carried out in North American settings. Validation outside of these settings is warranted.    This was a retrospective database study using data from newb...

Robot assisted laser-interstitial thermal therapy with iSYS1 and Visualase: how I do it.

BACKGROUND: Laser-interstitial thermal therapy (LITT) is an ablative treatment based on a surgically implanted laser-emitting catheter to induce a focal ablation of the pathological tissue. The main indications in neurosurgery are primary brain tumors, metastases, radiation necrosis, and pediatric brain tumors. Several approaches have been proposed to implant the laser-emitting catheter, both in f...

Remote Care Assistance in Emergency Department Based on Smart Medical.

Smart medical care is user-centric, medical information is the main line, and big data, Internet of Things, cloud computing, artificial intelligence, ...

Adversarial attack vulnerability of medical image analysis systems: Unexplored factors.

Adversarial attacks are considered a potentially serious security threat for machine learning systems. Medical image analysis (MedIA) systems have rec...

Predicting malaria epidemics in Burkina Faso with machine learning.

Accurately forecasting the case rate of malaria would enable key decision makers to intervene months before the onset of any outbreak, potentially sav...

Human breast milk-based nutritherapy: A blueprint for pediatric healthcare.

Human Breast Milk (HBM) is a storehouse of micronutrients, macronutrients, immune factors, microbiota and numerous other bioactive macromolecules. Ful...

Decreased neutrophil-mediated bacterial killing in COVID-19 patients.

The coronavirus disease COVID-19 was first described in December 2019. The peripheral blood of COVID-19 patients have increased numbers of neutrophils...

Indian citizen's perspective about side effects of COVID-19 vaccine - A machine learning study.

BACKGROUND AND AIMS: Ever since the vaccination drive for COVID-19 has started in India, the citizens have been sharing their views on social media ab...

Deep Learning Assisted Neonatal Cry Classification Support Vector Machine Models.

Neonatal infants communicate with us through cries. The infant cry signals have distinct patterns depending on the purpose of the cries. Preprocessing...

Machine learning accurately classifies neural responses to rhythmic speech vs. non-speech from 8-week-old infant EEG.

Currently there are no reliable means of identifying infants at-risk for later language disorders. Infant neural responses to rhythmic stimuli may off...

Detecting acute bilirubin encephalopathy in neonates based on multimodal MRI with deep learning.

BACKGROUND: Differentiating acute bilirubin encephalopathy (ABE) from non-ABE in neonates with hyperbilirubinemia (HB) from routine magnetic resonance...

Digital technologies to improve the precision of paediatric growth disorder diagnosis and management.

Paediatric disorders of impaired linear growth are challenging to manage, in part because of delays in the identification of pathological short statur...

Reliable Prediction Models Based on Enriched Data for Identifying the Mode of Childbirth by Using Machine Learning Methods: Development Study.

BACKGROUND: The use of artificial intelligence has revolutionized every area of life such as business and trade, social and electronic media, educatio...

Modeling and optimizing callus growth and development in Cannabis sativa using random forest and support vector machine in combination with a genetic algorithm.

Plant callus is generally considered to be a mass of undifferentiated cells and can be used for secondary metabolite production, physiological studies...

Deep learning-based prediction of future growth potential of technologies.

Research papers are a repository of information on the various elements that make up science and technology R&D activities. Generating knowledge maps ...

Hybridized neural networks for non-invasive and continuous mortality risk assessment in neonates.

Premature birth is the primary risk factor in neonatal deaths, with the majority of extremely premature babies cared for in neonatal intensive care un...

Detecting Medical Misinformation on Social Media Using Multimodal Deep Learning.

In 2019, outbreaks of vaccine-preventable diseases reached the highest number in the US since 1992. Medical misinformation, such as antivaccine conten...

Study on the identification and evaluation of growth years for Paris polyphylla var. yunnanensis using deep learning combined with 2DCOS.

Paris polyphylla var. yunnanensis, as perennial plants, its quality is closely related to growth period. Different harvest years determine the dry mat...

The potential of AI in cancer care and research.

Current applications of artificial intelligence (AI), machine learning, and deep learning in cancer research and clinical care are highly diverse-from...

The current and future roles of artificial intelligence in pediatric radiology.

Artificial intelligence (AI) is a broad and complicated concept that has begun to affect many areas of medicine, perhaps none so much as radiology. Wh...