Pilot study using machine learning to improve estimation of physical abuse prevalence.

Background: International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes have been shown to underestimate physical abuse prevalence. Machine learning models are capable of efficiently processing a wide variety of data and may provide better estimates of abuse.

Objective: To achieve proof of concept applying machine learning to identify codes associated with abuse.

Physical abuse re-reporting during the COVID-19 pandemic: The kids are not okay.

Background: Child physical abuse (PA) is a significant societal concern with limited research into predictors of re-reports.

Objective: Our research explores correlations between sociodemographic variables and re-reported PA. Our aim was to characterize populations at higher risk and identify changes in presentation during the COVID-19 pandemic.

The Deterioration Risk Index: Developing and Piloting a Machine Learning Algorithm to Reduce Pediatric Inpatient Deterioration.

Objectives: Develop and deploy a disease cohort-based machine learning algorithm for timely identification of hospitalized pediatric patients at risk for clinical deterioration that outperforms our existing situational awareness program.

Design: Retrospective cohort study.

Setting: Nationwide Children's Hospital, a freestanding, quaternary-care, academic children's hospital in Columbus, OH.

Prioritizing Hormone Therapy Over Vigabatrin as the First Treatment for Infantile Spasms: A Quality Improvement Initiative.

Background And Objectives: Infantile spasms (IS) are early childhood seizures with potentially devastating consequences. Standard therapies (adrenocorticotropic hormone [ACTH], high-dose prednisolone, and vigabatrin) are strongly recommended as the first treatment for IS. Although this recommendation comes without preference for one standard therapy over another, early remission rates are higher with hormone therapy (ACTH and high-dose prednisolone) when compared with vigabatrin.

Patient-centered design criteria for wearable seizure detection devices.

Introduction: Epilepsy is a common neurological condition. Seizure diary reports and patient- or caregiver-reported seizure counts are often inaccurate and underestimated. Many caregivers express stress and anxiety about the patient with epilepsy having seizures when they are not present.

Lung nodule CAD software as a second reader: a multicenter study.

Rationale And Objectives: The purpose of this multicenter, multireader study was to evaluate the performance of computed tomography (CT) lung nodule computer-aided detection (CAD) software as a second reader.

Methods And Materials: The study involved 109 patients from four sites. The data were collected from a variety of multidetector CT scanners and had different scan parameters.

Application of statistical modeling to optimize a coastal water quality monitoring program.

The long-term water quality monitoring program implemented by the Massachusetts Water Resources Authority in 1992 is extensive and has provide substantial understanding of the seasonality of the waters in both Boston Harbor and Massachusetts Bay and the response to improvements in effluent quality and offshore transfer of the effluent in September 2000. The monitoring program was designed with limited knowledge of spatial and temporal variability and long-term trends within the system. This led to an extensive spatial and temporal sampling program.

Transcriptional analysis of protective antigen-stimulated PBMC from non-human primates vaccinated with the anthrax vaccine absorbed.

The transcriptional responses in recombinant protective antigen (PA)-stimulated peripheral blood mononuclear cells (PBMCs) from Anthrax Vaccine Absorbed (AVA)-vaccinated rhesus macaques were evaluated using Affymetrix HGU133 Plus 2.0 GeneChips. PBMCs from animals vaccinated at 0, 4, and 26 weeks were harvested at week 30, stimulated with PA, and RNA isolated.