AIMC Topic: Radiography

Clear Filters Showing 991 to 1000 of 1117 articles

Bone age assessment from articular surface and epiphysis using deep neural networks.

Mathematical biosciences and engineering : MBE
Bone age assessment is of great significance to genetic diagnosis and endocrine diseases. Traditional bone age diagnosis mainly relies on experienced radiologists to examine the regions of interest in hand radiography, but it is time-consuming and ma...

Deep Learning-Enabled Detection of Pneumoperitoneum in Supine and Erect Abdominal Radiography: Modeling Using Transfer Learning and Semi-Supervised Learning.

Korean journal of radiology
OBJECTIVE: Detection of pneumoperitoneum using abdominal radiography, particularly in the supine position, is often challenging. This study aimed to develop and externally validate a deep learning model for the detection of pneumoperitoneum using sup...

[Development and Application of Medical Imaging Analysis Platform Based on Radiomics and Machine Learning Technologies].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
OBJECTIVE: In order to solve the technical problems, clinical researchers face the process of medical imaging analysis such as data labeling, feature extraction and algorithm selection, a medical imaging oriented multi-disease research platform based...

ENRICHing medical imaging training sets enables more efficient machine learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Deep learning (DL) has been applied in proofs of concept across biomedical imaging, including across modalities and medical specialties. Labeled data are critical to training and testing DL models, but human expert labelers are limited. In...

The rise of artificial intelligence reading of chest X-rays for enhanced TB diagnosis and elimination.

The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease
We provide an overview of the latest evidence on computer-aided detection (CAD) software for automated interpretation of chest radiographs (CXRs) for TB detection. CAD is a useful tool that can assist in rapid and consistent CXR interpretation for TB...

Artificial Intelligence Solution for Chest Radiographs in Respiratory Outpatient Clinics: Multicenter Prospective Randomized Clinical Trial.

Annals of the American Thoracic Society
Artificial intelligence (AI)-assisted diagnosis imparts high accuracy to chest radiography (CXR) interpretation; however, its benefit for nonradiologist physicians in detecting lung lesions on CXR remains unclear. To investigate whether AI assistan...

DECIDE-AI: a new reporting guideline and its relevance to artificial intelligence studies in radiology.

Clinical radiology
DECIDE-AI is a new, stage-specific reporting guideline for the early and live clinical evaluation of decision-support systems based on artificial intelligence (AI). It answers a need for more attention to the human factors influencing clinical AI per...