AIMC Topic: Radiography, Thoracic

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Development of an artificial intelligence-based algorithm for the detection of left atrial enlargement from feline thoracic radiographs.

The veterinary quarterly
A heart-convolutional neural network (heart-CNN) was developed and tested for the automatic detection of left atrial enlargement (LAE) from feline thoracic radiographs. A retrospective and multicenter study was performed. Right lateral and dorso-vent...

Ensemble deep learning architectures for detecting pulmonary tuberculosis in chest X-rays.

Scientific reports
Tuberculosis (TB) remains a major global health challenge, causing approximately 1.4 million deaths annually. In many high-burden regions, limited access to expert radiological interpretation leads to delayed or missed diagnoses. To address this, we ...

Utilizing AI CAD for early pandemic screening in chest radiographs.

Scientific reports
To investigate the potential application of existing artificial intelligence (AI) software in diagnosing COVID-19 (coronavirus disease 2019) and other pneumonia-related radiographic findings with the unprecedented challenge by COVID-19 pandemic, leve...

CIRCA: comprehensible online system in support of chest X-rays-based screening by COVID-19 example.

Scientific reports
Chest X-rays (CXRs) are widely used for diagnosing respiratory diseases, including the recent example of COVID-19. Supervised deep learning techniques can help detect cases faster and monitor disease progression. However, they are usually developed u...

Multiscale attention generative adversarial networks for lesion synthesis in chest X-ray images.

Scientific reports
Recent advancements in deep learning have led to significant improvements in pneumoconiosis diagnosis from chest X-rays (CXR). However, these models typically require large training datasets, which are challenging to collect due to the rarity of the ...

Evaluating the impact of AI assistance on decision-making in emergency doctors interpreting chest X-rays: a multi-reader multi-case study.

Emergency medicine journal : EMJ
BACKGROUND: Artificial intelligence (AI) tools could assist emergency doctors interpreting chest X-rays to inform urgent care. However, the impact of AI assistance on clinical decision-making, a precursor to enhanced care and patient outcomes, remain...

Trustworthy pneumonia detection in chest X-ray imaging through attention-guided deep learning.

Scientific reports
Pneumonia remains a significant global health threat, especially among children, the elderly, and immunocompromised individuals. Chest X-ray (CXR) imaging is commonly used for diagnosis, but manual interpretation is prone to errors and variability. T...

Artificial intelligence improves detection and classification of pulmonary venous hypertension related to left ventricular diastolic dysfunction by chest radiography.

Scientific reports
Isolated-Left Ventricular Diastolic Dysfunction [LVDD] ranges (and may progress) from preclinical asymptomatic, symptomatic-LVDD, to LVDD-predominate Heart Failure [HF] presentations; if recognized early, LVDD progression might be preventable. Curren...