Corrections to "Automatic Croup Diagnosis Using Cough Sound Recognition".

Area of Science:

• Biomedical Engineering
• Artificial Intelligence in Medicine
• Respiratory Medicine

Background:

• Croup diagnosis in children can be challenging.
• Objective methods for croup diagnosis are needed.
• Automated analysis of cough sounds shows promise for respiratory illness detection.

Purpose of the Study:

• To present corrections to shareholder information for a previously published paper.
• To ensure accuracy in the citation and attribution of the original work on automatic croup diagnosis.

Main Methods:

• This document does not present new research methods.
• It serves as a corrigendum to a published IEEE Transactions on Biomedical Engineering paper.

Main Results:

• Shareholder information in the original publication requires correction.
• Ensures accurate referencing and credit for the research on cough sound recognition for croup diagnosis.

Conclusions:

• Accurate shareholder information is crucial for scientific integrity.
• This correction maintains the credibility of the original study on automated croup diagnosis.