tuberculosis

Welcome to the blog on Artificial Intelligence of
the European Society of Radiology

This blog aims at bringing educational and critical perspectives on AI to readers. It should help imaging professionals to learn and keep up to date with the technologies being developed in this rapidly evolving field.

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Latest posts

A deep learning model using chest X-ray to identify TB and NTM-LD patients

The authors of this study aimed to evaluate whether artificial intelligence, specifically a deep neural network (DNN), was able to distinguish between tuberculosis (TB) or nontuberculous mycobacterial lung disease (NTM-LD) patients through chest X-rays (CXRs) from suspected mycobacterial lung disease. A total of 1,500 CXRs from two hospitals were retrospectively collected and evaluated. They determined that the developed DNN model

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Deep learning–based automated detection algorithm for active pulmonary tuberculosis on chest radiographs: diagnostic performance in systematic screening of asymptomatic individuals

Chest radiographs (CRs) have long been used as one of the screening tests for pulmonary tuberculosis (TB). However, the interpretation of a large number of CRs is time-consuming and labor-intensive. To overcome this difficulty, we developed the deep-learning-based automated detection (DLAD) for active pulmonary TB detection and performed out-of-sample testing in the consecutively collected 20.135 CRs from 19.686 servicepersons. As

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A deep learning model using chest X-ray to identify TB and NTM-LD patients

The authors of this study aimed to evaluate whether artificial intelligence, specifically a deep neural network (DNN), was able to distinguish between tuberculosis (TB) or nontuberculous mycobacterial lung disease (NTM-LD) patients through chest X-rays (CXRs) from suspected mycobacterial lung disease. A total of 1,500 CXRs from two hospitals were retrospectively collected and evaluated. They determined that the developed DNN model

Read More →

Deep learning–based automated detection algorithm for active pulmonary tuberculosis on chest radiographs: diagnostic performance in systematic screening of asymptomatic individuals

Chest radiographs (CRs) have long been used as one of the screening tests for pulmonary tuberculosis (TB). However, the interpretation of a large number of CRs is time-consuming and labor-intensive. To overcome this difficulty, we developed the deep-learning-based automated detection (DLAD) for active pulmonary TB detection and performed out-of-sample testing in the consecutively collected 20.135 CRs from 19.686 servicepersons. As

Read More →

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