Pediatrics

Game theoretical trajectory planning enhances social acceptability of robots by humans.

Since humans and robots are increasingly sharing portions of their operational spaces, experimental evidence is needed to ascertain the safety and social acceptability of robots in human-populated environments. Although several studies have aimed at devising strategies for robot trajectory planning to perform safe motion in populated environments, a few efforts have measured to what extent a robot...

Predicting childhood and adolescent attention-deficit/hyperactivity disorder onset: a nationwide deep learning approach.

Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous disorder with a high degree of psychiatric and physical comorbidity, which complicates its diagnosis in childhood and adolescence. We analyzed registry data from 238,696 persons born and living in Sweden between 1995 and 1999. Several machine learning techniques were used to assess the ability of registry data to inform the diagnos...

On usage of artificial intelligence for predicting mortality during and post-pregnancy: a systematic review of literature.

BACKGROUND: Care during pregnancy, childbirth and puerperium are fundamental to avoid pathologies for the mother and her baby. However, health issues ...

From computer to bedside, involving neonatologists in artificial intelligence models for neonatal medicine.

In recent years, data have become the main driver of medical innovation. With increased availability and decreased price of storage and computing powe...

Use of Robot-Assisted Gait Training in Pediatric Patients with Cerebral Palsy in an Inpatient Setting-A Randomized Controlled Trial.

Robot-assisted gait training (RAGT) provides a task-based support of walking using exoskeletons. Evidence shows moderate, but positive effects in the ...

Review of robot-assisted laparoscopic surgery in management of infant congenital urology: Advances and limitations in utilization and learning.

As robotic-assisted (RAL) surgery expanded to treat pediatric congenital disease, infant anatomy and physiology posed unique challenges that prompted ...

Iterative Reconstruction: State-of-the-Art and Future Perspectives.

Image reconstruction processing in computed tomography (CT) has evolved tremendously since its creation, succeeding at optimizing radiation dose while...

Children's views on artificial intelligence and digital twins for the daily management of their asthma: a mixed-method study.

New technologies enable the creation of digital twin systems (DTS) combining continuous data collection from children's home and artificial intelligen...

Artificial intelligence-driven wearable technologies for neonatal cardiorespiratory monitoring. Part 2: artificial intelligence.

BACKGROUND: With the development of Artificial Intelligence (AI) techniques, smart health monitoring, particularly neonatal cardiorespiratory monitori...

Artificial Intelligence in Pediatric Nephrology-A Call for Action.

Artificial intelligence is playing an increasingly important role in many fields of clinical care to assist health care providers in patient managemen...

Multi-layer perceptron classification & quantification of neuronal survival in hypoxic-ischemic brain image slices using a novel gradient direction, grey level co-occurrence matrix image training.

Hypoxic ischemic encephalopathy (HIE) is a major global cause of neonatal death and lifelong disability. Large animal translational studies of hypoxic...

Epistemic Rights and Responsibilities of Digital Simulacra for Biomedicine.

Big data and AI have enabled digital simulation for prediction of future health states or behaviors of specific individuals, populations or humans in ...

Artificial intelligence in cancer research and precision medicine: Applications, limitations and priorities to drive transformation in the delivery of equitable and unbiased care.

Artificial intelligence (AI) has experienced explosive growth in oncology and related specialties in recent years. The improved expertise in data capt...

Efficacy of robot-assisted hepaticojejunostomy and laparoscopic-assisted hepaticojejunostomy in pediatric congenital choledochal dilatation: a system review and meta-analysis.

PURPOSE: The efficacy of robot-assisted hepaticojejunostomy (RAHJ) and laparoscopic-assisted hepaticojejunostomy (LAHJ) in children with congenital ch...

Deep-learning-based personalized prediction of absolute neutrophil count recovery and comparison with clinicians for validation.

Neutropenia and its complications are major adverse effects of cytotoxic chemotherapy. The time to recovery from neutropenia varies from patient to pa...

Global stability of a continuous bioreactor model under persistent variation of the dilution rate.

In this work, the global stability of a continuous bioreactor model is studied, with the concentrations of biomass and substrate as state variables, a...

[User-oriented needs assessment of the potential use of assistive robots in direct nursing care: A mixed methods study].

User-oriented needs assessment of the potential use of assistive robots in direct nursing care: A mixed methods study So far, hardly any robots have...

Robot Technology for the Elderly and the Value of Veracity: Disruptive Technology or Reinvigorating Entrenched Principles?

The implementation of care robotics in care settings is identified by some authors as a disruptive innovation, in the sense that it will upend the pra...

Develop a hybrid machine learning model for promoting microbe biomass production.

Since the cultivation condition of microbe biomass production (mycelia yield) involves a variety of factors, it's a laborious process to obtain the op...

Effectiveness of cone-beam computed tomography-generated cephalograms using artificial intelligence cephalometric analysis.

Lateral cephalograms and related analysis constitute representative methods for orthodontic treatment. However, since conventional cephalometric radio...