Pediatrics

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

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Hope for the best prepare for the worst: acute kidney disease and catastrophic comorbidities (a case report).

It is evident that Acute Kidney Injury (AKI) is an independent risk factor for both the survival of ...

AI-directed formulation strategy design initiates rational drug development.

Rational drug development would be impossible without selecting the appropriate formulation route. H...

Impact of a trace mineral injection at weaning on growth, behavior, and inflammatory, antioxidant, and immune responses of beef calves.

Two experiments evaluated the effects of an injectable trace mineral (ITM) solution at weaning on tr...

Predicting candidate biomarkers for COVID-19 associated with leukemia in children.

Since the COVID-19 pandemic, a significant number of pediatric leukemia patients have shown to have ...

Enhancing drug discovery and patient care through advanced analytics with the power of NLP and machine learning in pharmaceutical data interpretation.

This study delves into the transformative potential of Machine Learning (ML) and Natural Language Pr...

Data-driven discovery of the interplay between genetic and environmental factors in bacterial growth.

A complex interplay of genetic and environmental factors influences bacterial growth. Understanding ...

Large language models facilitating modern molecular biology and novel drug development.

The latest breakthroughs in information technology and biotechnology have catalyzed a revolutionary ...

Artificial intelligence and sexual reproductive health and rights: a technological leap towards achieving sustainable development goal target 3.7.

Target 3.7 of the Sustainable Development Goals (SDGs) aims for universal access to sexual and repro...

Sentiment analysis of pilgrims using CNN-LSTM deep learning approach.

Crowd management refers to the management and control of masses at specific locations. A Hajj gather...

Smart interfaces to assist the operator in the context of industry 4.0 with a 5S human-centric approach.

This paper explores the integration of haptic gloves and virtual reality (VR) environments to enhanc...

Allelopathic effects of six alfalfa varieties at three stubbles on the germination, seedling and root growth of green foxtail and barnyardgrass.

Alfalfa (Medicago sativa) is known to release allelopathic substances to affect the germination and ...

Predicting preterm birth using electronic medical records from multiple prenatal visits.

This study aimed to predict preterm birth in nulliparous women using machine learning and easily acc...

Evaluation of Pregnancy Risks in Women with Subchorionic Hematoma Using Machine Learning Models.

BACKGROUND Subchorionic hematoma (SCH) can lead to blood accumulation and potentially affect pregnan...

Artificial intelligence in pediatric allergy research.

UNLABELLED: Atopic dermatitis, food allergy, allergic rhinitis, and asthma are among the most common...

Using artificial intelligence to predict post-operative outcomes in congenital heart surgeries: a systematic review.

INTRODUCTION: Congenital heart disease (CHD) represents the most common group of congenital anomalie...

Neuropathology of focal epilepsy: the promise of artificial intelligence and digital Neuropathology 3.0.

Focal lesions of the human neocortex often cause drug-resistant epilepsy, yet ​surgical resection of...

Development and validation of machine learning models for predicting venous thromboembolism in colorectal cancer patients: A cohort study in China.

BACKGROUND: With advancements in healthcare, traditional VTE risk assessment tools are increasingly ...

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