Call for Decision Support for Electrocardiographic Alarm Administration Among Neonatal Intensive Care Unit Staff: Multicenter, Cross-Sectional Survey.

Background: Previous studies have shown that electrocardiographic (ECG) alarms have high sensitivity and low specificity, have underreported adverse events, and may cause neonatal intensive care unit (NICU) staff fatigue or alarm ignoring. Moreover, prolonged noise stimuli in hospitalized neonates can disrupt neonatal development.

Objective: The aim of the study is to conduct a nationwide, multicenter, large-sample cross-sectional survey to identify current practices and investigate the decision-making requirements of health care providers regarding ECG alarms.

Childhood Leukemia Classification via Information Bottleneck Enhanced Hierarchical Multi-Instance Learning.

Leukemia classification relies on a detailed cytomorphological examination of Bone Marrow (BM) smear. However, applying existing deep-learning methods to it is facing two significant limitations. Firstly, these methods require large-scale datasets with expert annotations at the cell level for good results and typically suffer from poor generalization.

Artificial intelligence promotes shared decision-making through recommending tests to febrile pediatric outpatients.

Background: To promote the shared decision-making (SDM) between patients and doctors in pediatric outpatient departments, this study was designed to validate artificial intelligence (AI) -initiated medical tests for children with fever.

Methods: We designed an AI model, named Xiaoyi, to suggest necessary tests for a febrile child before visiting a pediatric outpatient clinic. We calculated the sensitivity, specificity, and F1 score to evaluate the efficacy of Xiaoyi's recommendations.

Racial differences in the associations of urinary phthalate metabolites with depression risk.

Objective: This study aimed to investigate the composite effects of different kinds of phthalates on depression risk in the U.S population.

Methods: 11731 participants were included from the National Health and Nutrition Examination Survey (NHANES), a national cross-sectional survey.

SPRSound: Open-Source SJTU Paediatric Respiratory Sound Database.

It has proved that the auscultation of respiratory sound has advantage in early respiratory diagnosis. Various methods have been raised to perform automatic respiratory sound analysis to reduce subjective diagnosis and physicians' workload. However, these methods highly rely on the quality of respiratory sound database.

Using artificial intelligence to reduce queuing time and improve satisfaction in pediatric outpatient service: A randomized clinical trial.

Introduction: Complicated outpatient procedures are associated with excessive paperwork and long waiting times. We aimed to shorten queuing times and improve visiting satisfaction.

Methods: We developed an artificial intelligence (AI)-assisted program named .

A 2.66 µW Clinician-Like Cardiac Arrhythmia Watchdog Based on P-QRS-T for Wearable Applications.

A wearable electrocardiogram (ECG) device is an effective tool for managing cardiovascular diseases. This paper presents a low power clinician-like cardiac arrhythmia watchdog (CAW) for wearable ECG devices. The CAW is based on a novel P-QRS-T detection algorithm that makes use of clinical features to identify abnormalities.

Establishment of a Simple Pediatric Lower Respiratory Tract Infections Database Based on the Structured Electronic Medical Records.

Objective: This study aimed to establish a pediatric lower respiratory tract infections (PLRTIs) database based on the structured electronic medical records (SEMRs), to provide a brief overview and the usage process of the SEMRs and the database.

Methods: All the medical information is recorded by a clinical information system developed by Eureka Systems Company. A plugin of the software was used to set the properties of items of the SEMR.

The Relationship Between Daily Dietary Intake of Fiber and Short Sleep Duration in the Presence of Di(2-Ethylhexyl) Phthalate: A Population-Based Study.

Objective: This study aimed to evaluate the relationship between daily dietary intake of fiber (DDIF) and short sleep duration (SSD) in the presence of di(2-ethylhexyl) phthalate.

Methods: Data of 13,634 participants in this study were collected from the National Health and Nutrition Examination Survey (NHANES). The sum of urinary mono-2-ethyl-5-carboxypentyl phthalate, mono-(2-ethyl-5-hydroxyhexyl) phthalate, mono-(2-ethyl)-hexyl phthalate, and mono-(2-ethyl-5-oxohexyl) phthalate was used to evaluate the level of di(2-ethylhexyl) phthalate (DEHP) exposure.

Automatic Detection of Secundum Atrial Septal Defect in Children Based on Color Doppler Echocardiographic Images Using Convolutional Neural Networks.

Secundum atrial septal defect (ASD) is one of the most common congenital heart diseases (CHDs). This study aims to evaluate the feasibility and accuracy of automatic detection of ASD in children based on color Doppler echocardiographic images using convolutional neural networks. In this study, we propose a fully automatic detection system for ASD, which includes three stages.

Standard Echocardiographic View Recognition in Diagnosis of Congenital Heart Defects in Children Using Deep Learning Based on Knowledge Distillation.

Standard echocardiographic view recognition is a prerequisite for automatic diagnosis of congenital heart defects (CHDs). This study aims to evaluate the feasibility and accuracy of standard echocardiographic view recognition in the diagnosis of CHDs in children using convolutional neural networks (CNNs). A new deep learning-based neural network method was proposed to automatically and efficiently identify commonly used standard echocardiographic views.

Quality and efficiency of a standardized e-handover system for pediatric nursing: A prospective interventional study.

Aim: This study examined the effect on pediatric nursing handover quality and efficiency when a standardized e-handover system was implemented.

Background: Handover quality is an important aspect of nursing quality management; however, handover quality among nursing staff is poor.

Methods: A prospective interventional study was carried out in a general pediatrics ward from December 2019 to November 2020.

The Associations of Caesarean Delivery With Risk of Wheezing Diseases and Changes of T Cells in Children.

Objectives: This study aimed to assess the associations of caesarean delivery (CD) with risk of wheezing diseases and changes of immune cells in children.

Design: The cross-sectional study was conducted between May, 2020 and April, 2021.

Setting And Participants: The study was conducted in Shanghai Children's Medical Center, Shanghai, China.

Pre-Consultation System Based on the Artificial Intelligence Has a Better Diagnostic Performance Than the Physicians in the Outpatient Department of Pediatrics.

Artificial intelligence (AI) has been deeply applied in the medical field and has shown broad application prospects. Pre-consultation system is an important supplement to the traditional face-to-face consultation. The combination of the AI and the pre-consultation system can help to raise the efficiency of the clinical work.

Mycoplasma pneumoniae infection prediction model for hospitalized community-acquired pneumonia children.

Objectives: We sought to develop a nomogram to predict Mycoplasma pneumoniae (Mp) infection among hospitalized children with community-acquired pneumonia (CAP) and compare it with another model developed from age and duration of fever.

Methods: Data on 5904 CAP children who were enrolled at Shanghai Children's Medical Center were retrospectively collected and divided into a training set (n = 4133) and a validation set (n = 1771). The model's performance was determined by concordance index (C-index), calibration curves, Brier scores, and decision curve analyses (DCAs).

LungAttn: advanced lung sound classification using attention mechanism with dual TQWT and triple STFT spectrogram.

. Auscultation of lung sound plays an important role in the early diagnosis of lung diseases. This work aims to develop an automated adventitious lung sound detection method to reduce the workload of physicians.

Development and Evaluation of a Leukemia Diagnosis System Using Deep Learning in Real Clinical Scenarios.

Leukemia is the most common malignancy affecting children. The morphologic analysis of bone marrow smears is an important initial step for diagnosis. Recent publications demonstrated that artificial intelligence is able to classify blood cells but a long way from clinical use.

Machine Learning for Early Warning of Septic Shock in Children With Hematological Malignancies Accompanied by Fever or Neutropenia: A Single Center Retrospective Study.

Objectives: The purpose of this article was to establish and validate clinically applicable septic shock early warning model (SSEW model) that can identify septic shock in hospitalized children with onco-hematological malignancies accompanied with fever or neutropenia.

Methods: Data from EMRs were collected from hospitalized pediatric patients with hematological and oncological disease at Shanghai Children's Medical Center. Medical records of patients (>30 days and <19 years old) with fever (≥38°C) or absolute neutrophil count (ANC) below 1.

Artificial Intelligence for Screening Chinese Electronic Medical Record and Biobank Information.

To establish a structured and integrated platform of clinical data and biobank data, and a client to retrieve these data. Initially, the hospital information system (HIS) and biobank information system (BIS) were integrated through the patients' ID numbers. Then, natural language processing (NLP) was used to process the integrated unstructured clinical information.

Artificial intelligence-assisted reduction in patients' waiting time for outpatient process: a retrospective cohort study.

Background: Many studies suggest that patient satisfaction is significantly negatively correlated with the waiting time. A well-designed healthcare system should not keep patients waiting too long for an appointment and consultation. However, in China, patients spend notable time waiting, and the actual time spent on diagnosis and treatment in the consulting room is comparatively less.

Is there possibility of vertical transmission of COVID-19: a systematic review.

In order to investigate the clinical features of pregnant women and their neonates with coronavirus disease 2019 (COVID-19) and the evidence of vertical transmission of COVID-19, we retrieved studies included in PubMed, Medline and Chinese databases from January 1, 2000 to October 25, 2020 using relevant terms, such as 'COVID-19', 'vertical transmission' . in 'Title/Abstract'. Case reports and case series were included according to the inclusion and exclusion criteria.