Pediatrics

Sentiment analysis of Indonesian tweets on COVID-19 and COVID-19 vaccinations.

BACKGROUND: Sentiments and opinions regarding COVID-19 and the COVID-19 vaccination on Indonesian-language Twitter are scarcely reported in one comprehensive study, and thus were aimed at our study. We also analyzed fake news and facts, and Twitter engagement to understand people's perceptions and beliefs that determine public health literacy.

Reply to: "Addressing Chatbots as Artificial Intelligence Aids in Pediatric Pathology".

Single-port robotic-assisted laparoscopic synchronous surgery in pediatric patent processus vaginalis.

PURPOSE: Patent processus vaginalis (PPV) is usually observed in pediatric abdominal surgery; however, robotic single-port surgery in repairing proces...

Machine learning for enhanced prognostication: predicting 30-day outcomes following posterior fossa decompression surgery for Chiari malformation type I in a pediatric cohort.

OBJECTIVE: Chiari malformation type I (CM-I) is a congenital disorder occurring in 0.1% of the population. In symptomatic cases, surgery with posterio...

Reinforcement Learning Algorithms and Applications in Healthcare and Robotics: A Comprehensive and Systematic Review.

Reinforcement learning (RL) has emerged as a dynamic and transformative paradigm in artificial intelligence, offering the promise of intelligent decis...

Towards quantifying biomarkers for respiratory distress in preterm infants: Machine learning on mid infrared spectroscopy of lipid mixtures.

Neonatal respiratory distress syndrome (nRDS) is a challenging condition to diagnose which can lead to delays in receiving appropriate treatment. Mid ...

AI in radiology: Legal responsibilities and the car paradox.

The integration of AI in radiology raises significant legal questions about responsibility for errors. Radiologists fear AI may introduce new legal ch...

Using Social Media and Artificial Intelligence to Find Your Purpose.

These days, the distractions of the digital world often obscure the journey to discover one's purpose. Yet these distractions hold clues to that very ...

Prediction of polyspecificity from antibody sequence data by machine learning.

Antibodies are generated with great diversity in nature resulting in a set of molecules, each optimized to bind a specific target. Taking advantage of...

Identifying pediatric heart murmurs and distinguishing innocent from pathologic using deep learning.

OBJECTIVE: To develop a deep learning algorithm to perform multi-class classification of normal pediatric heart sounds, innocent murmurs, and patholog...

Development and evaluation of an artificial intelligence for bacterial growth monitoring in clinical bacteriology.

In clinical bacteriology laboratories, reading and processing of sterile plates remain a significant part of the routine workload (30%-40% of the plat...

Identification of Congenital Valvular Murmurs in Young Patients Using Deep Learning-Based Attention Transformers and Phonocardiograms.

One in every four newborns suffers from congenital heart disease (CHD) that causes defects in the heart structure. The current gold-standard assessmen...

Deep Learning for Automated Measurement of Total Cardiac Volume for Heart Transplantation Size Matching.

Total Cardiac Volume (TCV)-based size matching using Computed Tomography (CT) is a novel technique to compare donor and recipient heart size in pediat...

Prediction of adverse cardiovascular events in children using artificial intelligence-based electrocardiogram.

BACKGROUND: Convolutional neural networks (CNNs) have emerged as a novel method for evaluating heart failure (HF) in adult electrocardiograms (ECGs). ...

Classifying early infant feeding status from clinical notes using natural language processing and machine learning.

The objective of this study is to develop and evaluate natural language processing (NLP) and machine learning models to predict infant feeding status ...

A deep learning framework for identifying and segmenting three vessels in fetal heart ultrasound images.

BACKGROUND: Congenital heart disease (CHD) is one of the most common birth defects in the world. It is the leading cause of infant mortality, necessit...

Social robotics as an adjuvant during the hospitalization process in pediatric oncology patients.

OBJECTIVE: To describe the experience of implementing social robotics as an adjuvant during the hospitalization process in pediatric oncology patients...

Research on precise phenotype identification and growth prediction of lettuce based on deep learning.

In recent years, precision agriculture, driven by scientific monitoring, precise management, and efficient use of agricultural resources, has become t...

Machine learning prediction model of major adverse outcomes after pediatric congenital heart surgery: a retrospective cohort study.

BACKGROUND: Major adverse postoperative outcomes (APOs) can greatly affect mortality, hospital stay, care management and planning, and quality of life...

Purely robotic ileocystoplasty in children: why not? First case in Spain.

INTRODUCTION: We present the first case of pediatric ileocystoplasty using a purely robotic approach in Spain.