Deep learning (DL) can predict and enhance MS lesions on unenhanced MRI scans, according to a new study published in Radiology.
Deep learning can improve the quality of coronary CT angiography (CCTA) images, according to a new study published in Academic Radiology.
AI can identify women at a high risk of developing breast cancer more accurately than existing prediction models, according to a new study published in Radiology.
Researchers have developed an AI algorithm that can identify cancer cells in digital pathology images, sharing their findings in EBioMedicine.
A new imaging technique that uses deep learning technology can identify tumors in colorectal tissue samples with 100% accuracy, according to findings published in Theranostics.
AI models can be trained to evaluate chest x-rays as well as radiologists, according to a new study published by Radiology. Specialist-approved reference standards played a crucial role in the team’s research.
Patients getting chest CT scans for lung cancer screenings can also be measured for heart disease thanks to AI, according to a new study presented at RSNA 2019 in Chicago.
Deep learning-based prediction models can help healthcare providers diagnose small pulmonary nodules, according to a new study published in Academic Radiology.
Convolutional neural networks (CNNs) can be trained to detect lung nodules on chest x-rays, according to a new study published in Artificial Intelligence in Medicine.
The United States is expected to experience a massive shortage of psychiatrists within the next five years. According to some researchers, however, AI technology could ease some of that burden.
Lunit, a medical software company based out of South Korea, has gained CE certification for its newest chest x-ray analysis solution, Lunit INSIGHT CXR.
Deep learning models can be trained to predict lymph node metastasis in breast cancer patients, according to new findings published in Radiology.