Publications by authors named "Qiuting Zheng"

Article Synopsis
  • - The study evaluates the effectiveness of a new AI system, MOM-ClaSeg, in helping radiologists detect lung abnormalities from chest X-ray images more accurately and efficiently.
  • - Over 36,000 chest X-rays were analyzed, comparing traditional double readings by two radiologists with a single reading enhanced by AI, showing notable improvements in diagnostic accuracy and speed with AI assistance.
  • - Results indicate that using AI as the first reader significantly boosts diagnostic accuracy by 1.49% and sensitivity by 10.95%, while also cutting average reading time by about 54.70%.
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Tuberculosis (TB) remains one of the major infectious diseases in the world with a high incidence rate. Drug-resistant tuberculosis (DR-TB) is a key and difficult challenge in the prevention and treatment of TB. Early, rapid, and accurate diagnosis of DR-TB is essential for selecting appropriate and personalized treatment and is an important means of reducing disease transmission and mortality.

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Background: Pulmonary nodular consolidation (PN) and pulmonary cavity (PC) may represent the two most promising imaging signs in differentiating multidrug-resistant (MDR)-pulmonary tuberculosis (PTB) from drug-sensitive (DS)-PTB. However, there have been concerns that literature described radiological feature differences between DS-PTB and MDR-PTB were confounded by that MDR-PTB cases tend to have a longer history. This study seeks to further clarify this point.

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Recently, COVID-19 has spread in more than 100 countries and regions around the world, raising grave global concerns. COVID-19 transmits mainly through respiratory droplets and close contacts, causing cluster infections. The symptoms are dominantly fever, fatigue, and dry cough, and can be complicated with tiredness, sore throat, and headache.

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