Application of deep learning for bronchial asthma diagnostics using respiratory sound recordings.

Methods of computer-assisted diagnostics that utilize deep learning techniques on recordings of respiratory sounds have been developed to diagnose bronchial asthma. In the course of the study an anonymous database containing audio files of respiratory sound recordings of patients suffering from different respiratory diseases and healthy volunteers has been accumulated and used to train the software and control its operation. The database consists of 1,238 records of respiratory sounds of patients and 133 records of volunteers.

Cardiometabolic risk factors among children and adolescents with overweight and Class 1 obesity: A cross-sectional study. Insights from stratification of Class 1 obesity.

Context: Severe childhood obesity is associated with increased prevalence of cardiometabolic risk factors (CMRFs). Among children with Class 1 obesity, higher BMI may indicate greater cardiometabolic risk. Class 1 obesity reflects a wide spectrum of BMI values.

Status of North American Graduate Programs in Periodontics Providing Laser Education and Clinical Training: A Cross-Sectional Survey.

The aim of this cross-sectional study was to evaluate the status of laser use and training in the U.S. and Canadian graduate periodontology programs.

Remote Analysis of Respiratory Sounds in Patients With COVID-19: Development of Fast Fourier Transform-Based Computer-Assisted Diagnostic Methods.

Background: Respiratory sounds have been recognized as a possible indicator of behavior and health. Computer analysis of these sounds can indicate characteristic sound changes caused by COVID-19 and can be used for diagnostics of this illness.

Objective: The aim of the study is to develop 2 fast, remote computer-assisted diagnostic methods for specific acoustic phenomena associated with COVID-19 based on analysis of respiratory sounds.

Long-Term Health Impacts of Wildfire Exposure: A Retrospective Study Exploring Hospitalization Dynamics Following the 2016 Wave of Fires in Israel.

Background: Climate-related events, including wildfires, which adversely affect human health, are gaining the growing attention of public-health officials and researchers. Israel has experienced several disastrous fires, including the wave of fires in November 2016 that led to the evacuation of 75,000 people. The fires lasted six days (22-27 November) with no loss of life or significant immediate health impacts.