Pediatrics

Potential for Machine Learning in Burn Care.

Burn-related injuries are a leading cause of morbidity across the globe. Accurate assessment and tre...

[Problems to be solved in the development from the perspective of future application scenarios of telesurgery].

Telemedicine, which integrates medicine, communication, engineering, information and other disciplin...

[Development and thoughts of digestive endoscopy in children].

After nearly 40 years of development, digestive endoscopy in children has been widely applied, and i...

[Applications and future prospects of artificial intelligence in neonatology].

Antegrade Colonic Enema Channels in Pediatric Patients Using Appendix or Cecal Flap: A Comparative Robotic Open Series.

We present perioperative outcomes of a single-center experience with robot-assisted antegrade colon...

Systematic Review and Meta-Analysis of Pediatric Robot-Assisted Laparoscopic Pyeloplasty.

To perform a systematic review (SR) and meta-analysis (MA) of outcomes of robot-assisted laparoscop...

Heart Murmurs in Children: Evaluation and Management.

Up to 8.6% of infants and 80% of children have a heart murmur during their early years of life. The ...

Use of real-time artificial intelligence in detection of abnormal image patterns in standard sonographic reference planes in screening for fetal intracranial malformations.

OBJECTIVES: To develop and validate an artificial intelligence system, the Prenatal ultrasound diagn...

Machine Learning Used to Compare the Diagnostic Accuracy of Risk Factors, Clinical Signs and Biomarkers and to Develop a New Prediction Model for Neonatal Early-onset Sepsis.

BACKGROUND: Current strategies for risk stratification and prediction of neonatal early-onset sepsis...

[Research and development of intelligent medical equipment and internationalization of acupuncture and moxibustion: thoughts from researchers of acupuncture robot].

Under the background of artificial intelligence, the internationalization of acupuncture and moxibus...

Artificial Intelligence and the Practice of Neurology in 2035: The Neurology Future Forecasting Series.

High-quality health care delivery relies on a complex orchestration of the flow of patient data. Inc...

Development and Internal Validation of Machine Learning Algorithms for Predicting Hyponatremia After TJA.

BACKGROUND: The development of hyponatremia after total joint arthroplasty (TJA) may lead to several...

Deep learning-based automatic tumor burden assessment of pediatric high-grade gliomas, medulloblastomas, and other leptomeningeal seeding tumors.

BACKGROUND: Longitudinal measurement of tumor burden with magnetic resonance imaging (MRI) is an ess...

Developing a Data Driven Approach for Early Detection of SIRS in Pediatric Intensive Care Using Automatically Labeled Training Data.

Critical care can benefit from analyzing data by machine learning approaches for supporting clinical...

What is the best method for long-term survival analysis?

In the Cox proportional hazards regression model, which is the most commonly used model in survival ...

Robot-assisted rehabilitation for children with neurological disabilities: Results of the Italian consensus conference CICERONE.

BACKGROUND: The use of robotic technologies in pediatric rehabilitation has seen a large increase, b...

Competencies for the Use of Artificial Intelligence in Primary Care.

The artificial intelligence (AI) revolution has arrived for the health care sector and is finally pe...

Megarrectosigmoides por constipación crónica idiopática, sigmoidectomía con robot en el paciente pediátrico. Primer caso en México.

We present the first pediatric case of Da Vinci Xi robot-assisted video sigmoidectomy in a 9-year-ol...

A Case of Well Leg Compartment Syndrome After Robot-assisted Laparoscopic Prostatectomy:With Review.

Robot-assisted laparoscopic prostatectomy (RALP) for prostate cancer was introduced in 2000 and rapi...

AI Tools Poised to Improve Patient Health Care.

Technologies to provide early predictions of breast cancer risk, to identify which hospital patients...

Development and Applications of Interoperable Biomedical Ontologies for Integrative Data and Knowledge Representation and Multiscale Modeling in Systems Medicine.

The data FAIR Guiding Principles state that all data should be Findable, Accessible, Interoperable, ...